This document describes a context-aware content-based recommendation framework called contextual eVSM. The framework is an extension of an earlier content-based recommendation model called eVSM that used distributional semantics. Contextual eVSM incorporates contextual information to make more accurate recommendations by taking into account factors like task, company, and mood. It models both positive and negative user preferences using a quantum logic-inspired approach. The framework was presented at the EC-WEB 2013 conference in Prague.
Intelligenza Artificiale e Social Media - Monitoraggio della Farnesina e La M...Cataldo Musto
Convegno a Porte Chiuse dell'Associazione Italiana per l'Intelligenza Artificiale insieme al Ministero per gli Affari Esteri e la Cooperazione Internazionale - 30 Giugno 2021
Exploring the Effects of Natural Language Justifications in Food Recommender ...Cataldo Musto
Cataldo Musto, Alain D. Starke, Christoph Trattner, Amon Rapp, and Giovanni Semeraro. 2021. Exploring the Effects of Natural Language Justifications in Food Recommender Systems. In Proceedings of the 29th ACM
Conference on User Modeling, Adaptation and Personalization (UMAP ’21), June 21–25, 2021, Utrecht, Netherlands. ACM, New York, NY, USA, 11 pages. https://doi.org/10.1145/3450613.3456827
Exploiting Distributional Semantics Models for Natural Language Context-aware...Cataldo Musto
The document proposes a methodology to generate context-aware natural language justifications for recommender systems by exploiting distributional semantics models. It involves learning a vector space representation of contexts, identifying the most suitable review excerpts given an item and context, and combining excerpts to form a justification. The goal is to produce justifications that vary based on different consumption contexts and are independent of the underlying recommendation model.
Towards a Knowledge-aware Food Recommender System Exploiting Holistic User Mo...Cataldo Musto
This document presents a knowledge-aware food recommender system that uses holistic user models. It aims to address limitations of content-based and collaborative filtering approaches. The proposed system uses a profiler to build comprehensive user profiles incorporating demographics, behaviors, health data and domain knowledge. Recipes are then filtered and ranked using this user information and food knowledge rules. An evaluation with 200 MTurk participants found users with health goals preferred recipes recommended by the holistic model over popular recipes. The study provides initial evidence the approach can better support healthy eating goals.
Intelligenza Artificiale e Social Media - Monitoraggio della Farnesina e La M...Cataldo Musto
Convegno a Porte Chiuse dell'Associazione Italiana per l'Intelligenza Artificiale insieme al Ministero per gli Affari Esteri e la Cooperazione Internazionale - 30 Giugno 2021
Exploring the Effects of Natural Language Justifications in Food Recommender ...Cataldo Musto
Cataldo Musto, Alain D. Starke, Christoph Trattner, Amon Rapp, and Giovanni Semeraro. 2021. Exploring the Effects of Natural Language Justifications in Food Recommender Systems. In Proceedings of the 29th ACM
Conference on User Modeling, Adaptation and Personalization (UMAP ’21), June 21–25, 2021, Utrecht, Netherlands. ACM, New York, NY, USA, 11 pages. https://doi.org/10.1145/3450613.3456827
Exploiting Distributional Semantics Models for Natural Language Context-aware...Cataldo Musto
The document proposes a methodology to generate context-aware natural language justifications for recommender systems by exploiting distributional semantics models. It involves learning a vector space representation of contexts, identifying the most suitable review excerpts given an item and context, and combining excerpts to form a justification. The goal is to produce justifications that vary based on different consumption contexts and are independent of the underlying recommendation model.
Towards a Knowledge-aware Food Recommender System Exploiting Holistic User Mo...Cataldo Musto
This document presents a knowledge-aware food recommender system that uses holistic user models. It aims to address limitations of content-based and collaborative filtering approaches. The proposed system uses a profiler to build comprehensive user profiles incorporating demographics, behaviors, health data and domain knowledge. Recipes are then filtered and ranked using this user information and food knowledge rules. An evaluation with 200 MTurk participants found users with health goals preferred recipes recommended by the holistic model over popular recipes. The study provides initial evidence the approach can better support healthy eating goals.
Natural Language Justifications for Recommender Systems Exploiting Text Summa...Cataldo Musto
The document describes a method for generating natural language justifications for recommender systems using text summarization and sentiment analysis techniques. It discusses prior approaches using descriptive properties or review-based features, and proposes a new approach that exploits automatic text summarization of user reviews. The proposed method involves extracting aspects from reviews, ranking aspects based on frequency, sentiment, and importance, and generating a summary justification using a centroid-based text summarization algorithm on filtered sentences from reviews. The goal is to provide a higher-quality justification by summarizing relevant information from multiple reviews.
Explanation Strategies - Advances in Content-based Recommender SystemCataldo Musto
This document summarizes a talk on content-based explanation strategies for recommender systems. It discusses using linked open data to provide explanations based on descriptive properties of recommended items and the user's preferences. It also discusses using sentiment analysis and text summarization of user reviews to justify recommendations. The talk presents the ExpLOD framework for generating explanations from linked open data and evaluates it in a user study comparing it to popularity-based and non-personalized baselines.
Justifying Recommendations through Aspect-based Sentiment Analysis of Users R...Cataldo Musto
The document describes a method for justifying recommendations through aspect-based sentiment analysis of users' reviews. It involves extracting aspects from reviews using natural language processing, ranking aspects by relevance and sentiment polarity, and generating a natural language justification using positive excerpts about high-ranking aspects. An experimental evaluation with 286 subjects compared justifications from different combinations of parameters and to a feature-based baseline. Results showed that review-based justifications scored higher than the baseline in terms of transparency, persuasion, engagement, trust and effectiveness.
Holistic User Modeling for Personalized Services in Smart CitiesCataldo Musto
The document describes a holistic user modeling approach for building personalized user profiles. Data is collected from various sources like social media, smartphones, and fitness trackers. This data is processed and used to populate facets of a user profile like demographics, interests, behaviors, and physical states. The profiles are made available via an API to power personalized services while giving users control over their data and privacy settings. A platform called Myrror was developed to create and manage these holistic user profiles.
A Framework for Holistic User Modeling Merging Heterogeneous Digital FootprintsCataldo Musto
A Framework for Holistic User Modeling Merging Heterogeneous Digital Footprints - HUM 2018 – Holistic User Modeling Workshop jointly held with
UMAP 2018 – 26th International
Conference on User Modeling,
Adaptation and Personalization
Singapore - July 8, 2018
Semantics-aware Recommender Systems Exploiting Linked Open Data and Graph-bas...Cataldo Musto
The document discusses semantics-aware recommender systems that exploit linked open data and graph-based features. It proposes combining heterogeneous groups of features, including popularity, collaborative, content, linked open data, and graph-based features to learn representations of items for recommendation. The approach is evaluated on movie recommendation datasets to assess the impact of incorporating linked open data and graph-based features into a hybrid recommendation framework.
A Multi-Criteria Recommender System Exploiting Aspect-based Sentiment Analysi...Cataldo Musto
The document describes a multi-criteria recommender system that exploits aspect-based sentiment analysis of user reviews. It involves a two-step methodology: 1) performing aspect extraction and sentiment analysis on user reviews using an algorithm based on SABRE to identify aspects, sub-aspects, and sentiment, and 2) creating and populating a multi-criteria data model with the extracted information and using it to generate recommendations. The system aims to develop a multi-criteria data model for recommendations without overwhelming users by automatically extracting product aspects and sentiments from reviews rather than requiring users to manually evaluate each aspect.
Recommender Systems based on Linked Open DataCataldo Musto
The document discusses using Linked Open Data for recommender systems. It begins with an overview of the Semantic Web and Linked Open Data, including the Linked Open Data cloud which contains billions of interconnected triples across thousands of datasets. A key dataset is DBpedia, which extracts structured data from Wikipedia pages. SPARQL can be used to query Linked Open Data and extract additional properties about items to enrich recommendation models. Linked Open Data can address limited content analysis in some systems by providing additional fine-grained features from datasets like DBpedia. It also naturally fits a graph-based data model that some recommender systems use.
Temporal and Holistic User Modeling Workshop - THUM@UMAP 2017Cataldo Musto
Opening presentation of the Workshop on Temporal and Holistic User Modeling - Merging Quantified Self with Semantic Content Analytics. Jointly held with UMAP 2017. Bratislava, Slovakia, July 2017.
Tuning Personalized PageRank for Semantics-aware Recommendations based on Lin...Cataldo Musto
This document summarizes a research paper presented at the ESWC 2017 conference on using linked open data to improve graph-based recommender systems. The researchers created a tripartite graph representation that encodes user preferences and item descriptive features from DBpedia. They investigated how the DBpedia features impact the representation quality and whether all features are equally important. They aim to automatically select the most promising features.
Semantics-aware Techniques for Social Media Analysis, User Modeling and Recom...Cataldo Musto
This document provides an overview and agenda for a tutorial on semantics-aware techniques for social media analysis, user modeling, and recommender systems. The tutorial will discuss how to represent content to improve information access and build new services for social media. It will cover why intelligent information access is needed to effectively cope with information overload, and how semantics can be introduced through natural language processing and by encoding endogenous and exogenous semantics. The agenda includes explaining recommendations, semantic user profiles based on social data, and semantic analysis of social streams.
AI-Powered Food Delivery Transforming App Development in Saudi Arabia.pdfTechgropse Pvt.Ltd.
In this blog post, we'll delve into the intersection of AI and app development in Saudi Arabia, focusing on the food delivery sector. We'll explore how AI is revolutionizing the way Saudi consumers order food, how restaurants manage their operations, and how delivery partners navigate the bustling streets of cities like Riyadh, Jeddah, and Dammam. Through real-world case studies, we'll showcase how leading Saudi food delivery apps are leveraging AI to redefine convenience, personalization, and efficiency.
In his public lecture, Christian Timmerer provides insights into the fascinating history of video streaming, starting from its humble beginnings before YouTube to the groundbreaking technologies that now dominate platforms like Netflix and ORF ON. Timmerer also presents provocative contributions of his own that have significantly influenced the industry. He concludes by looking at future challenges and invites the audience to join in a discussion.
Natural Language Justifications for Recommender Systems Exploiting Text Summa...Cataldo Musto
The document describes a method for generating natural language justifications for recommender systems using text summarization and sentiment analysis techniques. It discusses prior approaches using descriptive properties or review-based features, and proposes a new approach that exploits automatic text summarization of user reviews. The proposed method involves extracting aspects from reviews, ranking aspects based on frequency, sentiment, and importance, and generating a summary justification using a centroid-based text summarization algorithm on filtered sentences from reviews. The goal is to provide a higher-quality justification by summarizing relevant information from multiple reviews.
Explanation Strategies - Advances in Content-based Recommender SystemCataldo Musto
This document summarizes a talk on content-based explanation strategies for recommender systems. It discusses using linked open data to provide explanations based on descriptive properties of recommended items and the user's preferences. It also discusses using sentiment analysis and text summarization of user reviews to justify recommendations. The talk presents the ExpLOD framework for generating explanations from linked open data and evaluates it in a user study comparing it to popularity-based and non-personalized baselines.
Justifying Recommendations through Aspect-based Sentiment Analysis of Users R...Cataldo Musto
The document describes a method for justifying recommendations through aspect-based sentiment analysis of users' reviews. It involves extracting aspects from reviews using natural language processing, ranking aspects by relevance and sentiment polarity, and generating a natural language justification using positive excerpts about high-ranking aspects. An experimental evaluation with 286 subjects compared justifications from different combinations of parameters and to a feature-based baseline. Results showed that review-based justifications scored higher than the baseline in terms of transparency, persuasion, engagement, trust and effectiveness.
Holistic User Modeling for Personalized Services in Smart CitiesCataldo Musto
The document describes a holistic user modeling approach for building personalized user profiles. Data is collected from various sources like social media, smartphones, and fitness trackers. This data is processed and used to populate facets of a user profile like demographics, interests, behaviors, and physical states. The profiles are made available via an API to power personalized services while giving users control over their data and privacy settings. A platform called Myrror was developed to create and manage these holistic user profiles.
A Framework for Holistic User Modeling Merging Heterogeneous Digital FootprintsCataldo Musto
A Framework for Holistic User Modeling Merging Heterogeneous Digital Footprints - HUM 2018 – Holistic User Modeling Workshop jointly held with
UMAP 2018 – 26th International
Conference on User Modeling,
Adaptation and Personalization
Singapore - July 8, 2018
Semantics-aware Recommender Systems Exploiting Linked Open Data and Graph-bas...Cataldo Musto
The document discusses semantics-aware recommender systems that exploit linked open data and graph-based features. It proposes combining heterogeneous groups of features, including popularity, collaborative, content, linked open data, and graph-based features to learn representations of items for recommendation. The approach is evaluated on movie recommendation datasets to assess the impact of incorporating linked open data and graph-based features into a hybrid recommendation framework.
A Multi-Criteria Recommender System Exploiting Aspect-based Sentiment Analysi...Cataldo Musto
The document describes a multi-criteria recommender system that exploits aspect-based sentiment analysis of user reviews. It involves a two-step methodology: 1) performing aspect extraction and sentiment analysis on user reviews using an algorithm based on SABRE to identify aspects, sub-aspects, and sentiment, and 2) creating and populating a multi-criteria data model with the extracted information and using it to generate recommendations. The system aims to develop a multi-criteria data model for recommendations without overwhelming users by automatically extracting product aspects and sentiments from reviews rather than requiring users to manually evaluate each aspect.
Recommender Systems based on Linked Open DataCataldo Musto
The document discusses using Linked Open Data for recommender systems. It begins with an overview of the Semantic Web and Linked Open Data, including the Linked Open Data cloud which contains billions of interconnected triples across thousands of datasets. A key dataset is DBpedia, which extracts structured data from Wikipedia pages. SPARQL can be used to query Linked Open Data and extract additional properties about items to enrich recommendation models. Linked Open Data can address limited content analysis in some systems by providing additional fine-grained features from datasets like DBpedia. It also naturally fits a graph-based data model that some recommender systems use.
Temporal and Holistic User Modeling Workshop - THUM@UMAP 2017Cataldo Musto
Opening presentation of the Workshop on Temporal and Holistic User Modeling - Merging Quantified Self with Semantic Content Analytics. Jointly held with UMAP 2017. Bratislava, Slovakia, July 2017.
Tuning Personalized PageRank for Semantics-aware Recommendations based on Lin...Cataldo Musto
This document summarizes a research paper presented at the ESWC 2017 conference on using linked open data to improve graph-based recommender systems. The researchers created a tripartite graph representation that encodes user preferences and item descriptive features from DBpedia. They investigated how the DBpedia features impact the representation quality and whether all features are equally important. They aim to automatically select the most promising features.
Semantics-aware Techniques for Social Media Analysis, User Modeling and Recom...Cataldo Musto
This document provides an overview and agenda for a tutorial on semantics-aware techniques for social media analysis, user modeling, and recommender systems. The tutorial will discuss how to represent content to improve information access and build new services for social media. It will cover why intelligent information access is needed to effectively cope with information overload, and how semantics can be introduced through natural language processing and by encoding endogenous and exogenous semantics. The agenda includes explaining recommendations, semantic user profiles based on social data, and semantic analysis of social streams.
AI-Powered Food Delivery Transforming App Development in Saudi Arabia.pdfTechgropse Pvt.Ltd.
In this blog post, we'll delve into the intersection of AI and app development in Saudi Arabia, focusing on the food delivery sector. We'll explore how AI is revolutionizing the way Saudi consumers order food, how restaurants manage their operations, and how delivery partners navigate the bustling streets of cities like Riyadh, Jeddah, and Dammam. Through real-world case studies, we'll showcase how leading Saudi food delivery apps are leveraging AI to redefine convenience, personalization, and efficiency.
In his public lecture, Christian Timmerer provides insights into the fascinating history of video streaming, starting from its humble beginnings before YouTube to the groundbreaking technologies that now dominate platforms like Netflix and ORF ON. Timmerer also presents provocative contributions of his own that have significantly influenced the industry. He concludes by looking at future challenges and invites the audience to join in a discussion.
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slackshyamraj55
Discover the seamless integration of RPA (Robotic Process Automation), COMPOSER, and APM with AWS IDP enhanced with Slack notifications. Explore how these technologies converge to streamline workflows, optimize performance, and ensure secure access, all while leveraging the power of AWS IDP and real-time communication via Slack notifications.
Full-RAG: A modern architecture for hyper-personalizationZilliz
Mike Del Balso, CEO & Co-Founder at Tecton, presents "Full RAG," a novel approach to AI recommendation systems, aiming to push beyond the limitations of traditional models through a deep integration of contextual insights and real-time data, leveraging the Retrieval-Augmented Generation architecture. This talk will outline Full RAG's potential to significantly enhance personalization, address engineering challenges such as data management and model training, and introduce data enrichment with reranking as a key solution. Attendees will gain crucial insights into the importance of hyperpersonalization in AI, the capabilities of Full RAG for advanced personalization, and strategies for managing complex data integrations for deploying cutting-edge AI solutions.
Driving Business Innovation: Latest Generative AI Advancements & Success StorySafe Software
Are you ready to revolutionize how you handle data? Join us for a webinar where we’ll bring you up to speed with the latest advancements in Generative AI technology and discover how leveraging FME with tools from giants like Google Gemini, Amazon, and Microsoft OpenAI can supercharge your workflow efficiency.
During the hour, we’ll take you through:
Guest Speaker Segment with Hannah Barrington: Dive into the world of dynamic real estate marketing with Hannah, the Marketing Manager at Workspace Group. Hear firsthand how their team generates engaging descriptions for thousands of office units by integrating diverse data sources—from PDF floorplans to web pages—using FME transformers, like OpenAIVisionConnector and AnthropicVisionConnector. This use case will show you how GenAI can streamline content creation for marketing across the board.
Ollama Use Case: Learn how Scenario Specialist Dmitri Bagh has utilized Ollama within FME to input data, create custom models, and enhance security protocols. This segment will include demos to illustrate the full capabilities of FME in AI-driven processes.
Custom AI Models: Discover how to leverage FME to build personalized AI models using your data. Whether it’s populating a model with local data for added security or integrating public AI tools, find out how FME facilitates a versatile and secure approach to AI.
We’ll wrap up with a live Q&A session where you can engage with our experts on your specific use cases, and learn more about optimizing your data workflows with AI.
This webinar is ideal for professionals seeking to harness the power of AI within their data management systems while ensuring high levels of customization and security. Whether you're a novice or an expert, gain actionable insights and strategies to elevate your data processes. Join us to see how FME and AI can revolutionize how you work with data!
AI 101: An Introduction to the Basics and Impact of Artificial IntelligenceIndexBug
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CAKE: Sharing Slices of Confidential Data on BlockchainClaudio Di Ciccio
Presented at the CAiSE 2024 Forum, Intelligent Information Systems, June 6th, Limassol, Cyprus.
Synopsis: Cooperative information systems typically involve various entities in a collaborative process within a distributed environment. Blockchain technology offers a mechanism for automating such processes, even when only partial trust exists among participants. The data stored on the blockchain is replicated across all nodes in the network, ensuring accessibility to all participants. While this aspect facilitates traceability, integrity, and persistence, it poses challenges for adopting public blockchains in enterprise settings due to confidentiality issues. In this paper, we present a software tool named Control Access via Key Encryption (CAKE), designed to ensure data confidentiality in scenarios involving public blockchains. After outlining its core components and functionalities, we showcase the application of CAKE in the context of a real-world cyber-security project within the logistics domain.
Paper: https://doi.org/10.1007/978-3-031-61000-4_16
Programming Foundation Models with DSPy - Meetup SlidesZilliz
Prompting language models is hard, while programming language models is easy. In this talk, I will discuss the state-of-the-art framework DSPy for programming foundation models with its powerful optimizers and runtime constraint system.
HCL Notes and Domino License Cost Reduction in the World of DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-and-domino-license-cost-reduction-in-the-world-of-dlau/
The introduction of DLAU and the CCB & CCX licensing model caused quite a stir in the HCL community. As a Notes and Domino customer, you may have faced challenges with unexpected user counts and license costs. You probably have questions on how this new licensing approach works and how to benefit from it. Most importantly, you likely have budget constraints and want to save money where possible. Don’t worry, we can help with all of this!
We’ll show you how to fix common misconfigurations that cause higher-than-expected user counts, and how to identify accounts which you can deactivate to save money. There are also frequent patterns that can cause unnecessary cost, like using a person document instead of a mail-in for shared mailboxes. We’ll provide examples and solutions for those as well. And naturally we’ll explain the new licensing model.
Join HCL Ambassador Marc Thomas in this webinar with a special guest appearance from Franz Walder. It will give you the tools and know-how to stay on top of what is going on with Domino licensing. You will be able lower your cost through an optimized configuration and keep it low going forward.
These topics will be covered
- Reducing license cost by finding and fixing misconfigurations and superfluous accounts
- How do CCB and CCX licenses really work?
- Understanding the DLAU tool and how to best utilize it
- Tips for common problem areas, like team mailboxes, functional/test users, etc
- Practical examples and best practices to implement right away
OpenID AuthZEN Interop Read Out - AuthorizationDavid Brossard
During Identiverse 2024 and EIC 2024, members of the OpenID AuthZEN WG got together and demoed their authorization endpoints conforming to the AuthZEN API
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My slides at Nordic Testing Days 6.6.2024
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HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-und-domino-lizenzkostenreduzierung-in-der-welt-von-dlau/
DLAU und die Lizenzen nach dem CCB- und CCX-Modell sind für viele in der HCL-Community seit letztem Jahr ein heißes Thema. Als Notes- oder Domino-Kunde haben Sie vielleicht mit unerwartet hohen Benutzerzahlen und Lizenzgebühren zu kämpfen. Sie fragen sich vielleicht, wie diese neue Art der Lizenzierung funktioniert und welchen Nutzen sie Ihnen bringt. Vor allem wollen Sie sicherlich Ihr Budget einhalten und Kosten sparen, wo immer möglich. Das verstehen wir und wir möchten Ihnen dabei helfen!
Wir erklären Ihnen, wie Sie häufige Konfigurationsprobleme lösen können, die dazu führen können, dass mehr Benutzer gezählt werden als nötig, und wie Sie überflüssige oder ungenutzte Konten identifizieren und entfernen können, um Geld zu sparen. Es gibt auch einige Ansätze, die zu unnötigen Ausgaben führen können, z. B. wenn ein Personendokument anstelle eines Mail-Ins für geteilte Mailboxen verwendet wird. Wir zeigen Ihnen solche Fälle und deren Lösungen. Und natürlich erklären wir Ihnen das neue Lizenzmodell.
Nehmen Sie an diesem Webinar teil, bei dem HCL-Ambassador Marc Thomas und Gastredner Franz Walder Ihnen diese neue Welt näherbringen. Es vermittelt Ihnen die Tools und das Know-how, um den Überblick zu bewahren. Sie werden in der Lage sein, Ihre Kosten durch eine optimierte Domino-Konfiguration zu reduzieren und auch in Zukunft gering zu halten.
Diese Themen werden behandelt
- Reduzierung der Lizenzkosten durch Auffinden und Beheben von Fehlkonfigurationen und überflüssigen Konten
- Wie funktionieren CCB- und CCX-Lizenzen wirklich?
- Verstehen des DLAU-Tools und wie man es am besten nutzt
- Tipps für häufige Problembereiche, wie z. B. Team-Postfächer, Funktions-/Testbenutzer usw.
- Praxisbeispiele und Best Practices zum sofortigen Umsetzen
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
Contextual eVSM: a context-aware content-based recommendation framework based on distributional semantics
1. EC-WEB 2013 - 14th International Conference on Electronic Commerce and WebTechnologies
Prague (Czech Republich) - 28.08.13
Contextual eVSM: a context-aware content-based
recommendation framework based on
distributional semantics
Cataldo Musto, Giovanni Semeraro, Pasquale Lops, Marco de Gemmis
2. scenario.
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
3. Prague, EC-Web conference
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
4. dinner time
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
5. me and Pasquale like sushi.
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
6. what doesTripAdvisor suggest?
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
7. C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
8. Good Price
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
9. Good Reviews
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
10. ....Strasbourg?
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
11. 612 km far away.
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
12. 612 km far away.
Too much :-)
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
13. we ate pizza, as usual.
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
14. why did theTripAdvisor
recommendation engine fail?
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
15. it doesn’t take into account
contextual information.
context plays a key role in
several recommendation tasks.
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
16. C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
I attended last Sigur Ròs concert
in Rome, so I like them
17. C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
I attended last Sigur Ròs concert
in Rome, so I like them
but their ambient music is not good if I need
music recommendation for my running session!
18. a real-world recommendation
engine needs to take into account
contextual information
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
19. what is context?
• Over 150 definitions, spread across several
domains (Bazire and Brezillon, 2005)
• Recommender Systems area
• “A set of factors that have influence on user
perception and acceptance of a
particular item”
• A fixed set of dimensions with appropriate
attributes
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
20. what is context?
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
task
21. what is context?
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
task
22. what is context?
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
task company
23. what is context?
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
task company
24. what is context?
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
task moodcompany
25. what is context?
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
task company mood
26. a real-world recommendation
engine needs to take into account
contextual information
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
27. Our contribution
contextual eVSM
a context-aware content-based recommendation
framework based on distributional semantics
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
28. timeline
2013: contextual eVSM
2010-2012: eVSM(*)
a content-based recommendation framework
based on distributional semantics
context-aware extension of eVSM
(*) Cataldo Musto: Enhanced vector space
models for content-based recommender
systems. RecSys 2010: 361-364
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
29. C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
eVSM
a brief recap
30. eVSM
• Content-based Recommendation Framework
• (semantic) vector space representation based on
distributional models
• negative information modeled through quantum
negation operator
• recommendation seen as a form of similarity in vector
spaces
• four different profiling models
• cosine similarity to get the top-k recommendations
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
cornerstones
31. distributional models
(Firth, 1957)
Firth, J.R. A synopsis of linguistic theory
1930-1955. In Studies in Linguistic Analysis,
pp. 1-32, 1957.
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
cornerstone 1
32. “meaning
is its use”
L.Wittgenstein
(Austrian philosopher)
distributional semantics
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
33. insight
by analyzing large corpus of textual data it is possible
to infer information about the usage (about the meaning)
of the terms.
example
distributional models
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
34. distributional hypothesis
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
“terms that occur in similar
contexts share a similar meaning”
35. distributional models
c1 c2 c3 c4 c5 c6
rock ✔ ✔ ✔
post rock ✔ ✔
jazz ✔
classical ✔ ✔ ✔
term/context matrix (WordSpace)
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
36. distributional models
rock vs. post rock = good overlap
c1 c2 c3 c4 c5 c6
rock ✔ ✔ ✔
post rock ✔ ✔
jazz ✔
classical ✔ ✔ ✔
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
37. distributional models
rock vs. classical = no overlap
c1 c2 c3 c4 c5 c6
rock ✔ ✔ ✔
post rock ✔ ✔
jazz ✔
classical ✔ ✔ ✔
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
38. • Key: definition of what is the
‘context’
• Different granularities
are possible
• Document
• Paragraph
• Sentence
• Sliding window of words
distributional models
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
40. representation of documents (*)
can be inferred by combining the representation of
the terms (**) occurring in the document.
(*) documents = artists
(**) terms = tags
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
41. distributional models
c1 c2 c3 c4 c5 c6 c7 c8 c9
t2 ✔ ✔ ✔ ✔
t3 ✔ ✔ ✔
d1 ✔ ✔ ✔ ✔ ✔
term/context matrix (DocSpace)
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
42. Coldplay
Radiohead
Kings of Leon
Lady Gaga
example
DocSpace
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
43. distributional models
• Features
• semantic vector space representation of
terms and documents (user profiles and items !)
• light semantics, based on term co-occurrences in
large corpus of data
• based on distributional hypothesis
• totally unsupervised
• just based on the analysis of term distribution
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
44. quantum negation
(Widdows, 2007)
cornerstone 2
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
45. negation inVSMs
•Widdows proposed a different point
of view
• Negation view as a form of orthogonality
between vectors
• Vision inherited from Quantum Logic
state of the art
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
46. negation inVSMs
• Some theory
• Given vector a and vector b
• Through quantum negation it is possible to define a
vector a not b (a ∧¬b)
• Projection of vector a on the subspace
orthogonal to those generated by vector b
Quantum Negation
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
47. negation inVSMs
• Two terms can be considered as mutually unrelevant
if they never co-occur
• Two documents can be considered as mutually
unrelevant if they have no features in common
• No features in common scalar product = 0
•Orthogonality
Widdows’ insights
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
48. quantum negation
• Vector A models positive feedbacks
• Information about what a user likes
• Vector B models negative feedbacks
• Information about what a user does not like
• Vector A not B combines both information
sources
application to CBRS
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
49. recommendation step
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
cornerstone 3
50. ThresholdRatingItems
Higher weight given to the documents with higher rating
User Profiles
Weighted Random Indexing-based (w-RI)
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
51. VSM representation of wQN-based profile for user u
Positive User ProfileVector
Negative User ProfileVector
User Profiles
Weighted Quantum Negation-based (w-QN)
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
52. scenario
football news
sports news
politics news
politics news
user profile
Recommendation
task seen as
similarity
calculation
between vectors
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
53. scenario
football news
sports news
politics news
politics news
user profile
football and
sports news are
recommended to
the target user
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
54. size=400 - Movielens dataset
Gap always around 1%
84
84,75
85,5
86,25
87
p@1 P@3 P@5 P@10
84,7584,7
84,97
85,39
84,58
84,7
84,85
85,27
84,5
84,77
84,4384,47
85,5285,58
86,0185,94
eVSM VSM
LSI Bayes
experiment(*)
Cataldo Musto - Enhanced Vector Space Models for Content-based Recommender Systems - Ph.D. defense - University of Bari Aldo Moro, Italy - 08.06.12
(*) Cataldo Musto. Enhanced
Vector Space Models for
content-based
Recommender Systems.
Ph.D dissertation, 2012
55. 84
84,75
85,5
86,25
87
p@1 P@3 P@5 P@10
84,7584,7
84,97
85,39
84,58
84,7
84,85
85,27
84,5
84,77
84,4384,47
85,5285,58
86,0185,94
eVSM VSM
LSI Bayes
size=400 - Movielens dataset
Significant Improvement
Cataldo Musto - Enhanced Vector Space Models for Content-based Recommender Systems - Ph.D. defense - University of Bari Aldo Moro, Italy - 08.06.12
experiment(*) (*) Cataldo Musto. Enhanced
Vector Space Models for
content-based
Recommender Systems.
Ph.D dissertation, 2012
56. eVSM outperforms other state-of-the-art approaches
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
57. eVSM outperforms other state-of-the-art approaches
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
but it doesn’t take into account contextual information.
58. contextual eVSM
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
how to make the eVSM context-aware?
59. context-aware RSs
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
state of the art: pre and post-filtering
60. we implemented two
contextualization strategies
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
both pre and post-filtering
61. context-aware eVSM
•Microprofiling
•based on contextual pre-
filtering
•Insight: to filter data before building
user profiles, building a separate
user profile for each contextual
dimension
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
62. context-aware eVSM
•Contextual eVSM
•based on contextual post-
filtering
•Insight: to calculate un-
contextualized recommendation
and to re-rank them according
to contextual constraints
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
63. C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
if a user needs suggestions for a restaurant for a
romantic dinner, only her ratings expressed for
previous romantic dinners have to be taken
into account
micro-profiling
insight
64. C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
micro-profiling
context-aware eVSM
65. C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
micro-profiling
context-aware eVSM
user
66. C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
micro-profiling
context-aware eVSM
contextual dimension (e.g task)
and value (e.g. running)
67. C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
micro-profiling
context-aware eVSM
sum over all the items rated under that
specific contextual constraints
68. C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
micro-profiling
context-aware eVSM
weighted with the (normalized) rating
provided by the user
69. contextual eVSM
insight
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
context is just a factor that can (positively or
negatively) influence user preference on a certain item
70. contextual eVSM
insight
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
context is just a factor that can (positively or
negatively) influence user preference on a certain item
context-aware recommendation can be obtained by
combining an uncontextual user profile with a
vector space representation of the target context
71. C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
contextual eVSM
context-aware eVSM
72. C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
contextual eVSM
context-aware eVSM
user profile is the combination of two components
73. C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
contextual eVSM
context-aware eVSM
(1) uncontextual user profile
74. C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
contextual eVSM
context-aware eVSM
(2) vector space representation
of the context
75. C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
contextual eVSM
context-aware eVSM
weight of each component
76. C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
contextual eVSM
context-aware eVSM
if alpha = 1, we have
uncontextual recommendation
since context weight = 0 !
77. C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
contextual eVSM
context-aware eVSM
problem: how to build it ?
78. • For each contextual dimension, it exists a
set of terms that is descriptive of items
relevant in that specific context
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
context representation
assumptions
79. • For each contextual dimension, it exists a set of
terms that is descriptive of items relevant in
that specific context
• e.g. candlelight or seaview are relevant features if
I’m looking for a restaurant for a romantic night !
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
context representation
assumptions
80. C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
context representation
idea
to represent the context as the combination
of the terms occurring in the descriptions of the
items labeled as relevant under that specific
contextual situation
81. C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
context representation
formula
PRE-WRI is exactly the combination of the terms
occurring in the descriptions of the items labeled as
relevant under that specific contextual situation !
we adopted PRE-WRI as vector space representation of
the context
82. C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
rationale
contextual eVSM
if the user didn’t express any preference in that
specific context, the vector is null, so she will receive
uncontextual recommendation
83. C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
rationale
contextual eVSM
if the user didn’t express any preference in that
specific context, the vector is null, so she will receive
uncontextual recommendation
otherwise, a greater weight will be given to the
features that are informative and relevant in the
target context, that is to say, those contained in the
context vector!
84. experimental
evaluation.
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
85. •Experiments
• (1) Does contextual eVSM outperform eVSM ?
• (2) How does our approach performs with respect to
current literature?
experimental design
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
86. • Movie recommendation (IMDB data)
• 202 movies (textual features crawled from Wikipedia)
• 62 users and 1457 ratings
• 4 contextual dimensions
• TIME (weekend, weekday)
• PLACE (theather, home)
• COMPANION (alone, friends, boyfriend, family)
• MOVIE-RELATED (release week or not)
experimental design
dataset
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
87. • Dataset and experimental settings replicate
Adomavicius’ experiment (*)
• Evaluation over 9 different contextual settings
• Home, Friends, Non-release,Weekend,Weekday,
GBFriends,TheatherWeekend andTheatherFriends
• Experimental protocol: bootstrapping
• 29/30th of the data as training
• 1/30th as test
• Randomly generated, 500 runs
experimental design
settings
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
(*) G.Adomavicius et al. ,
Incorporating contextual
information in recommender
systems using a multi-
dimensional approach.ACM Trans.
Inf. Systems, 2005
88. • eVSM settings
• Uncontextual baselines
• WRI and WQN
• Pre-filtering
• PRE-WRI and PRE-WQN
• Post-filtering:
• CONTEXT-WRI and CONTEXT-WQN
• alpha=0.5, alpha=0.8
• 8 settings for each run
experimental design
parameters
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
89. experiment 1
selection of results - HOME segment
WRI
PRE-WRI
CONT-WRI-0.5
CONT-WRI-0.8
WQN
PRE-WQN
CONT-WQN-0.5
CONT-WQN-0.8
45 48,75 52,5 56,25 60
pre-filtering outperforms the baseline
(it’s an exception, in the other segments it doesn’t !)
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
90. experiment 1
selection of results - HOME segment
WRI
PRE-WRI
CONT-WRI-0.5
CONT-WRI-0.8
WQN
PRE-WQN
CONT-WQN-0.5
CONT-WQN-0.8
45 48,75 52,5 56,25 60
contextual eVSM improves the F1 measure
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
91. experiment 1
selection of results - HOME segment
WRI
PRE-WRI
CONT-WRI-0.5
CONT-WRI-0.8
WQN
PRE-WQN
CONT-WQN-0.5
CONT-WQN-0.8
45 48,75 52,5 56,25 60
alpha=0.8 better than alpha 0.5
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
92. experiment 1
selection of results - HOME segment
WRI
PRE-WRI
CONT-WRI-0.5
CONT-WRI-0.8
WQN
PRE-WQN
CONT-WQN-0.5
CONT-WQN-0.8
45 48,75 52,5 56,25 60
contextual eVSM with negation is the best setting
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
93. experiment 1
selection of results - FRIEND segment
WRI
PRE-WRI
CONT-WRI-0.5
CONT-WRI-0.8
WQN
PRE-WQN
CONT-WQN-0.5
CONT-WQN-0.8
45 47,5 50 52,5 55
similar outcomes
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
94. experiment 1
selection of results - FRIEND segment
WRI
PRE-WRI
CONT-WRI-0.5
CONT-WRI-0.8
WQN
PRE-WQN
CONT-WQN-0.5
CONT-WQN-0.8
45 47,5 50 52,5 55
pre-filtering doesn’t improve the accuracy
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
95. experiment 1
selection of results - FRIEND segment
WRI
PRE-WRI
CONT-WRI-0.5
CONT-WRI-0.8
WQN
PRE-WQN
CONT-WQN-0.5
CONT-WQN-0.8
45 47,5 50 52,5 55
contextual eVSM generally does
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
96. experiment 1
selection of results - FRIEND segment
WRI
PRE-WRI
CONT-WRI-0.5
CONT-WRI-0.8
WQN
PRE-WQN
CONT-WQN-0.5
CONT-WQN-0.8
45 47,5 50 52,5 55
contextual eVSM with negation and alpha=0.8 is always the best setting
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
97. experiment 1
selection of results - NON RELEASE segment
WRI
PRE-WRI
CONT-WRI-0.5
CONT-WRI-0.8
WQN
PRE-WQN
CONT-WQN-0.5
CONT-WQN-0.8
45 48 51 54 57
contextual eVSM with negation and alpha=0.8 is always the best setting
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
98. experiment 1
selection of results - NON RELEASE segment
WRI
PRE-WRI
CONT-WRI-0.5
CONT-WRI-0.8
WQN
PRE-WQN
CONT-WQN-0.5
CONT-WQN-0.8
45 48 51 54 57
typically, alpha=0.8 is better than alpha 0.5
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
99. experiment 1
selection of results - NON RELEASE segment
WRI
PRE-WRI
CONT-WRI-0.5
CONT-WRI-0.8
WQN
PRE-WQN
CONT-WQN-0.5
CONT-WQN-0.8
45 48 51 54 57
outcome: context has just a little influence on user perception and
acceptance. Uncontextual preferences are still the “core”.
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
100. experiment 1
selection of results - NON RELEASE segment
WRI
PRE-WRI
CONT-WRI-0.5
CONT-WRI-0.8
WQN
PRE-WQN
CONT-WQN-0.5
CONT-WQN-0.8
45 48 51 54 57
outcome: context has to be taken into account, but just a little!
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
101. experiment 1
selection of results - THEATHER segment
WRI
PRE-WRI
CONT-WRI-0.5
CONT-WRI-0.8
WQN
PRE-WQN
CONT-WQN-0.5
CONT-WQN-0.8
45 47,25 49,5 51,75 54
However, in some setting
contextual eVSM without negation is the best
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
102. experiment 1
selection of results - THEATHER segment
WRI
PRE-WRI
CONT-WRI-0.5
CONT-WRI-0.8
WQN
PRE-WQN
CONT-WQN-0.5
CONT-WQN-0.8
45 47,25 49,5 51,75 54
experiments showed a clear relationship between the amount of
negative ratings and the best configurations
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
103. experiment 1
selection of results - THEATHER segment
WRI
PRE-WRI
CONT-WRI-0.5
CONT-WRI-0.8
WQN
PRE-WQN
CONT-WQN-0.5
CONT-WQN-0.8
45 47,25 49,5 51,75 54
when the dataset is well balanced, cont-WQN outperforms cont-WRI,
otherwise when few negative data are available, cont-WRI is the best
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
104. experiment 1
selection of results - THEATHER+FRIENDS segment
WRI
PRE-WRI
CONT-WRI-0.5
CONT-WRI-0.8
WQN
PRE-WQN
CONT-WQN-0.5
CONT-WQN-0.8
40 41,75 43,5 45,25 47
contextual eVSM didn’t improve F1 measure
in just 1 contextual segment out of 9
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
105. experiment 1 - outcome
contextual eVSM improves the predictive accuracy of eVSM
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
106. experiment 2
comparison with state-of-the-art
HOME
FRIENDS
WEEKEND
THEATHER
NONRELEASE
WEEKDAY
GBFRIEND
THEAT-WEEK
THEAT-FRIENDS
37 45,25 53,5 61,75 70
comparison with Adomavicius’ approach based on CF
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
107. experiment 2
comparison with state-of-the-art
HOME
FRIENDS
WEEKEND
THEATHER
NONRELEASE
WEEKDAY
GBFRIEND
THEAT-WEEK
THEAT-FRIENDS
37 45,25 53,5 61,75 70
eVSM outperforms CF in 6 segments out of 9
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
108. experiment 2 - outcome
contextual eVSM improves the predictive accuracy
of state-of-the-art approaches based on CF
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
109. recap.
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
110. recap
• context-aware eVSM
• baseline: eVSM
• content-based recommendation framework
• distributional semantics + quantum negation
• evolution: contextual eVSM
• comparison of two approaches for context-aware eVSM
• exact pre-filtering and weighted post-filtering
• large experimental evaluation, comparison with state of the
art approaches
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
111. contextual eVSM overcomes
state-of-the-art approaches
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
112. future research.
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
113. evaluation with
different datasets
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
114. open knowledge sources and
linked data for CBRS.
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
115. evaluation with user-based metrics
(serendipity, novelty, unexpectedness)
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013
116. questions?
Cataldo Musto, Ph.D
cataldo.musto@uniba.it
C. Musto, G. Semeraro, P. Lops, M. de Gemmis. - Contextual eVSM: a context-aware content-based recommendation
framework based on distributional semantics - EC WEB 2013 - Prague, Czech Republic - 28.08.2013