The document discusses text categorization techniques, including supervised and unsupervised learning. It introduces several approaches to text categorization such as SVM, kNN, Naive Bayes, neural networks, and linear least squares fit. SVM is explained further as building a maximum-margin hyperplane to categorize data points in an Rn space according to their features. The motivation is to automatically classify and manage large amounts of online information.
This document provides an overview of a course on usability and interaction design. The course investigates how to design software that meets users' needs and goals by including usability throughout the development process. It covers principles of usability like learnability and efficiency. Students will learn how to design and conduct usability tests of a product to identify potential usability issues.
This is part 1 of the tutorial Xavier and Deepak gave at Recsys 2016 this year. You can find the second part http://www.slideshare.net/xamat/recsys-2016-tutorial-lessons-learned-from-building-reallife-recommender-systems
Smart meeting systems a survey of state of-the-artunyil96
Smart meeting systems aim to automatically record, analyze, and summarize meetings. The article surveys the state-of-the-art technologies in smart meeting systems, including their typical architecture, methods for capturing meetings through video, audio and other sensors, techniques for recognizing meeting content, processing meeting semantics, and evaluating system performance. It also discusses various open issues that could extend the capabilities of current smart meeting systems.
The document provides an overview of the user interface development process, including analysis, design, prototyping, and usability principles. It discusses tasks such as defining user profiles and scenarios, wireframing, information architecture, visual design, and standards compliance. Web 1.0 is contrasted with newer collaborative and interactive aspects of Web 2.0.
Discovering Common Motifs in Cursor Movement DataYandex
The document discusses research on discovering common motifs in mouse cursor movement data. It summarizes prior work on modeling post-click user behavior on search result pages. The researchers aim to automatically discover meaningful patterns (motifs) in cursor movement data without pre-defining complex features. They describe a pipeline to generate motif candidates, find frequent candidates, de-duplicate motifs, and apply various optimizations. Experimental results show motifs can improve relevance prediction and search result ranking. Motifs are also useful for characterizing attention patterns and predicting cognitive impairment.
Ask Me Any Rating: A Content-based Recommender System based on Recurrent Neur...Alessandro Suglia
Presentation for "Ask Me Any Rating: A Content-based Recommender System based on Recurrent Neural Networks" at the 7th Italian Information Retrieval Workshop.
See paper: http://ceur-ws.org/Vol-1653/paper_11.pdf
This document provides an overview of a course on usability and interaction design. The course investigates how to design software that meets users' needs and goals by including usability throughout the development process. It covers principles of usability like learnability and efficiency. Students will learn how to design and conduct usability tests of a product to identify potential usability issues.
This is part 1 of the tutorial Xavier and Deepak gave at Recsys 2016 this year. You can find the second part http://www.slideshare.net/xamat/recsys-2016-tutorial-lessons-learned-from-building-reallife-recommender-systems
Smart meeting systems a survey of state of-the-artunyil96
Smart meeting systems aim to automatically record, analyze, and summarize meetings. The article surveys the state-of-the-art technologies in smart meeting systems, including their typical architecture, methods for capturing meetings through video, audio and other sensors, techniques for recognizing meeting content, processing meeting semantics, and evaluating system performance. It also discusses various open issues that could extend the capabilities of current smart meeting systems.
The document provides an overview of the user interface development process, including analysis, design, prototyping, and usability principles. It discusses tasks such as defining user profiles and scenarios, wireframing, information architecture, visual design, and standards compliance. Web 1.0 is contrasted with newer collaborative and interactive aspects of Web 2.0.
Discovering Common Motifs in Cursor Movement DataYandex
The document discusses research on discovering common motifs in mouse cursor movement data. It summarizes prior work on modeling post-click user behavior on search result pages. The researchers aim to automatically discover meaningful patterns (motifs) in cursor movement data without pre-defining complex features. They describe a pipeline to generate motif candidates, find frequent candidates, de-duplicate motifs, and apply various optimizations. Experimental results show motifs can improve relevance prediction and search result ranking. Motifs are also useful for characterizing attention patterns and predicting cognitive impairment.
Ask Me Any Rating: A Content-based Recommender System based on Recurrent Neur...Alessandro Suglia
Presentation for "Ask Me Any Rating: A Content-based Recommender System based on Recurrent Neural Networks" at the 7th Italian Information Retrieval Workshop.
See paper: http://ceur-ws.org/Vol-1653/paper_11.pdf
Ask Me Any Rating: A Content-based Recommender System based on Recurrent Neur...Claudio Greco
Slides for the presentation of the paper "Ask Me Any Rating: A Content-based Recommender System based on Recurrent Neural Networks" at the 7th Italian Information Retrieval Workshop.
The document summarizes a research paper on DBLP Search Support Engine (SSE), a system that aims to provide intelligent and personalized search beyond traditional search engines. It extracts users' research interests based on publication frequency and recency using interest retention models. The system represents users and their interests using RDF and provides additional functionalities like query refinement, domain analysis and tracking based on users' interests. Future work includes improving the interest prediction model and providing a unified architecture for different system functions.
Model-Driven Engineering of User Interfaces: Promises, Successes, Failures, a...Jean Vanderdonckt
Model-driven engineering (MDE) of user interfaces consists in describing a user interface and aspects involved in it (e.g., task, domain, context of use) in models from which a final interface is produced. With one big win in mind: when the user’s requirements or the context of use change, the models change accordingly and so does the supporting user interface. Models and a method for developing user interfaces based on MDE are presented in this tutorial supporting forward engineering (a new interface is produced), reverse engineering (an existing interface is improved), and lateral engineering (an existing interface is adapted to a new context of use). Software supporting this method will be used based on UsiXML (User Interface eXten-sible Markup Language), a XML-compliant user interface description language.
This document discusses using Bayesian networks for predictive analysis and machine learning perspectives on data utilization. It provides an example of using Bayesian networks to accurately predict incident clearance time based on variables like type of incident, number of police/ambulance vehicles, number of injuries, and number of vehicles involved. The document also discusses applying Bayesian networks by collecting current situation data as evidence to perform inference on a constructed inference model.
CoMo Game Dev - usability and user experience methods Isa Jahnke
The Information Experience Laboratory (IE Lab) at the University of Missouri conducts usability and user experience research to improve learning technologies, information systems, and digital products. The IE Lab uses various methods like task analysis, think aloud protocols, surveys, focus groups, card sorting, and heuristic evaluations to test users' experiences. Insights from usability studies help create more effective and satisfying designs that are easier to use. The IE Lab works with clients across various fields and has tools for in-person and remote usability testing.
This document describes a system that extracts events from multiple data sources like text, images and videos. It constructs "event cubes" to organize the extracted information by dimensions like location and participants. The system allows users to search for events matching query criteria and recommends related events based on their attributes. It summarizes events and extracts visual concepts and patterns to provide richer event profiles to users.
1) The document discusses various ways that artificial intelligence can be applied to different phases of the software engineering lifecycle, including requirements specification, design, coding, testing, and estimation.
2) It provides examples of using techniques like natural language processing to clarify requirements, knowledge graphs to manage requirements information, and computational intelligence for requirements prioritization.
3) For design, the document discusses using intelligent agents to recommend patterns and designs to satisfy quality attributes from requirements and assist with assigning responsibilities to components.
Methodology for the Development of Vocal User InterfacesJean Vanderdonckt
Natural User Interfaces allow users to interact with systems similarly as they interact with people. Human communications occur, mostly, in an oral way, since personal dialogs to phone calls and more recently in complain or information systems; the tendency is to automate some of these activities so the user might complete tasks in a more efficient way. The necessity for having a methodology that supports the development of vocal interfaces is therefore taking interest on it. The objective for this sample paper is to establish a methodology and to describe a set of rules that might be used for developing a software tool to generate code for multiplatform vocal User Interfaces from models
The document provides an introduction to the course CS E4505 - Human Computer Interaction. It discusses what HCI is, its interdisciplinary nature, examples of computer systems that require interaction, and levels of interaction from individual to community use. It also outlines the goals and philosophy of the course, including grading criteria and an overview of the course textbook.
24 Hours of UX, 2023: Preventing the FutureJoshua Randall
On our current trajectory, the future of UX design will look much like the present, only worse. The gold rush mentality towards UX design as a “career” combined with Gresham’s Law (“bad money drives out good”) applied to design combined with automation from software platforms means we are increasing the pace at which bad designs proliferate. In this talk Joshua Randall will cite data from larger research companies like Baymard and Nielsen Norman Group as well as draw on examples from his career to paint a picture of the coming dystopia.
This document presents a reference framework for classifying software quality models. It proposes analyzing software quality using four "worlds": 1) Subject World, which defines what software quality is, 2) Usage World, which identifies user intentions and goals for quality, 3) System World, which specifies how quality will be represented and measured, and 4) Development World, which contains processes and tools to achieve quality objectives. Each world addresses a fundamental question about quality. The framework characterizes each model based on attributes within these worlds. It aims to provide a comprehensive way to analyze, compare, and develop software quality models.
This document discusses transparency issues with current metrics used to measure scientific impact, such as PageRank and Journal Impact Factor. It argues that these metrics lack transparency in their algorithms and are susceptible to gaming. As an alternative, it proposes altmetrics, which provide transparent, verifiable impact indicators linked to open data sources. Altmetrics track references and reuse of scholarly works both within and outside of academia. They aim to give a more comprehensive view of impact by measuring extra-academic usage and reuse of open scholarly content. The document calls for more transparent APIs and measures of reuse to better capture scientific impact.
On Tuesday 18 September 2007, Ben Shneiderman gave a talk at the Centre for HCI Design, City University London, on the topic of information visualisation for high-dimensional spaces. Over 100 people from industry and academia attended the talk.
http://hcid.soi.cty.ac.uk/
Studying user footprints in different online social networksIIIT Hyderabad
This document describes research on linking a user's accounts across multiple online social networks. It discusses the challenges in linking accounts as usernames and profiles can differ across networks. Existing techniques for linking are reviewed, along with their limitations. The paper then presents a new supervised learning approach to link Twitter and LinkedIn accounts based on similarity metrics for different profile fields. Evaluation shows the approach can accurately match accounts with 98% accuracy and discover new candidate matches for a given user profile.
Desney S. Tan is a researcher at Microsoft Research who specializes in human-computer interaction and physiological computing. He received his PhD from Carnegie Mellon University in 2004. His research interests include machine learning, mobile computing, sensors, and evaluation techniques to improve healthcare and digital experiences. He has received several awards for his research and currently manages groups at Microsoft Research focused on computational user experiences and human-computer interaction.
Desney S. Tan is a researcher at Microsoft Research who works on human-computer interaction and physiological computing. He received his PhD from Carnegie Mellon University in 2004. His research interests include machine learning, visualization, mobile computing, sensors, and evaluation techniques for improving healthcare and digital experiences. He has published extensively in top conferences and journals and holds several awards for his research contributions.
Ask Me Any Rating: A Content-based Recommender System based on Recurrent Neur...Claudio Greco
Slides for the presentation of the paper "Ask Me Any Rating: A Content-based Recommender System based on Recurrent Neural Networks" at the 7th Italian Information Retrieval Workshop.
The document summarizes a research paper on DBLP Search Support Engine (SSE), a system that aims to provide intelligent and personalized search beyond traditional search engines. It extracts users' research interests based on publication frequency and recency using interest retention models. The system represents users and their interests using RDF and provides additional functionalities like query refinement, domain analysis and tracking based on users' interests. Future work includes improving the interest prediction model and providing a unified architecture for different system functions.
Model-Driven Engineering of User Interfaces: Promises, Successes, Failures, a...Jean Vanderdonckt
Model-driven engineering (MDE) of user interfaces consists in describing a user interface and aspects involved in it (e.g., task, domain, context of use) in models from which a final interface is produced. With one big win in mind: when the user’s requirements or the context of use change, the models change accordingly and so does the supporting user interface. Models and a method for developing user interfaces based on MDE are presented in this tutorial supporting forward engineering (a new interface is produced), reverse engineering (an existing interface is improved), and lateral engineering (an existing interface is adapted to a new context of use). Software supporting this method will be used based on UsiXML (User Interface eXten-sible Markup Language), a XML-compliant user interface description language.
This document discusses using Bayesian networks for predictive analysis and machine learning perspectives on data utilization. It provides an example of using Bayesian networks to accurately predict incident clearance time based on variables like type of incident, number of police/ambulance vehicles, number of injuries, and number of vehicles involved. The document also discusses applying Bayesian networks by collecting current situation data as evidence to perform inference on a constructed inference model.
CoMo Game Dev - usability and user experience methods Isa Jahnke
The Information Experience Laboratory (IE Lab) at the University of Missouri conducts usability and user experience research to improve learning technologies, information systems, and digital products. The IE Lab uses various methods like task analysis, think aloud protocols, surveys, focus groups, card sorting, and heuristic evaluations to test users' experiences. Insights from usability studies help create more effective and satisfying designs that are easier to use. The IE Lab works with clients across various fields and has tools for in-person and remote usability testing.
This document describes a system that extracts events from multiple data sources like text, images and videos. It constructs "event cubes" to organize the extracted information by dimensions like location and participants. The system allows users to search for events matching query criteria and recommends related events based on their attributes. It summarizes events and extracts visual concepts and patterns to provide richer event profiles to users.
1) The document discusses various ways that artificial intelligence can be applied to different phases of the software engineering lifecycle, including requirements specification, design, coding, testing, and estimation.
2) It provides examples of using techniques like natural language processing to clarify requirements, knowledge graphs to manage requirements information, and computational intelligence for requirements prioritization.
3) For design, the document discusses using intelligent agents to recommend patterns and designs to satisfy quality attributes from requirements and assist with assigning responsibilities to components.
Methodology for the Development of Vocal User InterfacesJean Vanderdonckt
Natural User Interfaces allow users to interact with systems similarly as they interact with people. Human communications occur, mostly, in an oral way, since personal dialogs to phone calls and more recently in complain or information systems; the tendency is to automate some of these activities so the user might complete tasks in a more efficient way. The necessity for having a methodology that supports the development of vocal interfaces is therefore taking interest on it. The objective for this sample paper is to establish a methodology and to describe a set of rules that might be used for developing a software tool to generate code for multiplatform vocal User Interfaces from models
The document provides an introduction to the course CS E4505 - Human Computer Interaction. It discusses what HCI is, its interdisciplinary nature, examples of computer systems that require interaction, and levels of interaction from individual to community use. It also outlines the goals and philosophy of the course, including grading criteria and an overview of the course textbook.
24 Hours of UX, 2023: Preventing the FutureJoshua Randall
On our current trajectory, the future of UX design will look much like the present, only worse. The gold rush mentality towards UX design as a “career” combined with Gresham’s Law (“bad money drives out good”) applied to design combined with automation from software platforms means we are increasing the pace at which bad designs proliferate. In this talk Joshua Randall will cite data from larger research companies like Baymard and Nielsen Norman Group as well as draw on examples from his career to paint a picture of the coming dystopia.
This document presents a reference framework for classifying software quality models. It proposes analyzing software quality using four "worlds": 1) Subject World, which defines what software quality is, 2) Usage World, which identifies user intentions and goals for quality, 3) System World, which specifies how quality will be represented and measured, and 4) Development World, which contains processes and tools to achieve quality objectives. Each world addresses a fundamental question about quality. The framework characterizes each model based on attributes within these worlds. It aims to provide a comprehensive way to analyze, compare, and develop software quality models.
This document discusses transparency issues with current metrics used to measure scientific impact, such as PageRank and Journal Impact Factor. It argues that these metrics lack transparency in their algorithms and are susceptible to gaming. As an alternative, it proposes altmetrics, which provide transparent, verifiable impact indicators linked to open data sources. Altmetrics track references and reuse of scholarly works both within and outside of academia. They aim to give a more comprehensive view of impact by measuring extra-academic usage and reuse of open scholarly content. The document calls for more transparent APIs and measures of reuse to better capture scientific impact.
On Tuesday 18 September 2007, Ben Shneiderman gave a talk at the Centre for HCI Design, City University London, on the topic of information visualisation for high-dimensional spaces. Over 100 people from industry and academia attended the talk.
http://hcid.soi.cty.ac.uk/
Studying user footprints in different online social networksIIIT Hyderabad
This document describes research on linking a user's accounts across multiple online social networks. It discusses the challenges in linking accounts as usernames and profiles can differ across networks. Existing techniques for linking are reviewed, along with their limitations. The paper then presents a new supervised learning approach to link Twitter and LinkedIn accounts based on similarity metrics for different profile fields. Evaluation shows the approach can accurately match accounts with 98% accuracy and discover new candidate matches for a given user profile.
Desney S. Tan is a researcher at Microsoft Research who specializes in human-computer interaction and physiological computing. He received his PhD from Carnegie Mellon University in 2004. His research interests include machine learning, mobile computing, sensors, and evaluation techniques to improve healthcare and digital experiences. He has received several awards for his research and currently manages groups at Microsoft Research focused on computational user experiences and human-computer interaction.
Desney S. Tan is a researcher at Microsoft Research who works on human-computer interaction and physiological computing. He received his PhD from Carnegie Mellon University in 2004. His research interests include machine learning, visualization, mobile computing, sensors, and evaluation techniques for improving healthcare and digital experiences. He has published extensively in top conferences and journals and holds several awards for his research contributions.
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdfMalak Abu Hammad
Discover how MongoDB Atlas and vector search technology can revolutionize your application's search capabilities. This comprehensive presentation covers:
* What is Vector Search?
* Importance and benefits of vector search
* Practical use cases across various industries
* Step-by-step implementation guide
* Live demos with code snippets
* Enhancing LLM capabilities with vector search
* Best practices and optimization strategies
Perfect for developers, AI enthusiasts, and tech leaders. Learn how to leverage MongoDB Atlas to deliver highly relevant, context-aware search results, transforming your data retrieval process. Stay ahead in tech innovation and maximize the potential of your applications.
#MongoDB #VectorSearch #AI #SemanticSearch #TechInnovation #DataScience #LLM #MachineLearning #SearchTechnology
Climate Impact of Software Testing at Nordic Testing DaysKari Kakkonen
My slides at Nordic Testing Days 6.6.2024
Climate impact / sustainability of software testing discussed on the talk. ICT and testing must carry their part of global responsibility to help with the climat warming. We can minimize the carbon footprint but we can also have a carbon handprint, a positive impact on the climate. Quality characteristics can be added with sustainability, and then measured continuously. Test environments can be used less, and in smaller scale and on demand. Test techniques can be used in optimizing or minimizing number of tests. Test automation can be used to speed up testing.
Dr. Sean Tan, Head of Data Science, Changi Airport Group
Discover how Changi Airport Group (CAG) leverages graph technologies and generative AI to revolutionize their search capabilities. This session delves into the unique search needs of CAG’s diverse passengers and customers, showcasing how graph data structures enhance the accuracy and relevance of AI-generated search results, mitigating the risk of “hallucinations” and improving the overall customer journey.
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdfPaige Cruz
Monitoring and observability aren’t traditionally found in software curriculums and many of us cobble this knowledge together from whatever vendor or ecosystem we were first introduced to and whatever is a part of your current company’s observability stack.
While the dev and ops silo continues to crumble….many organizations still relegate monitoring & observability as the purview of ops, infra and SRE teams. This is a mistake - achieving a highly observable system requires collaboration up and down the stack.
I, a former op, would like to extend an invitation to all application developers to join the observability party will share these foundational concepts to build on:
Unlocking Productivity: Leveraging the Potential of Copilot in Microsoft 365, a presentation by Christoforos Vlachos, Senior Solutions Manager – Modern Workplace, Uni Systems
“An Outlook of the Ongoing and Future Relationship between Blockchain Technologies and Process-aware Information Systems.” Invited talk at the joint workshop on Blockchain for Information Systems (BC4IS) and Blockchain for Trusted Data Sharing (B4TDS), co-located with with the 36th International Conference on Advanced Information Systems Engineering (CAiSE), 3 June 2024, Limassol, Cyprus.
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...Neo4j
Leonard Jayamohan, Partner & Generative AI Lead, Deloitte
This keynote will reveal how Deloitte leverages Neo4j’s graph power for groundbreaking digital twin solutions, achieving a staggering 100x performance boost. Discover the essential role knowledge graphs play in successful generative AI implementations. Plus, get an exclusive look at an innovative Neo4j + Generative AI solution Deloitte is developing in-house.
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.
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
7. User Modeling(UM, 1986-2007, 11th) California Adaptive Hypermedia and Adaptive Web-Based Systems(AH, 2000-2008, 5th) Italy UM+AH = UMAP(2009, 17th) UMAP(Adaption, Personalization)
8. Title : [1]Construction of Ontology-Based User Model for Web Personalization (Cited: 9 times) H. Zhang, Y. Song, and H.T. Song, “Construction of ontology-based user model for web personalization,” Proceeding of the 11th international conference User Modeling 2007, pp. 67–76. UM2007
9. Authors: Hui Zhang, Yu Song, and Han-tao Song Motivation: to provide web information that matches a user’s personal interests Purpose: Application: personalized web browsing and search [1]Construction of Ontology-Based User Model for Web Personalization
11. Steps: 1.S-Log(Semantic-log):representing the semantics of the respective URL(from domain ontology) 2.Session analysis algorithm outcome : semantic session include thematic categories 3. IS = user’s new session=outcome B(IS):user ontology(beginning of the visit is empty) S(IS):structure of the site(automatically built) 4.O = B(IS) U O (O:global user’s ontology) [1]How(cont.)
12. :look up :union :ontology [1]How-Imagination of Ontology Global User Ontology
13. Each user has a graph: C_Graph(N, u)=<N, A>, N: nodes, A:arcs, u:user arc(s, t)=>label(s, t) = <dst, rst, hst, Tst> dst: semantic independence coefficient rst: semantic relevance coefficient hst: hit coefficient Tst: time coefficient s,t : concept [1]Pre-defined
14. Duration: 1997-2011 Title [1]Personalized News Recommendation Based on Click Behavior (Cited: 2 times) J. Liu, P. Dolan, and E.R. Pedersen, “Personalized news recommendation based on click behavior,” Proceeding of the 14th international conference on Intelligent User Interfaces, 2010, pp. 31–40. IUI 2010
15. Authors: Jiahui Liu, Peter Dolan, ElinRonby Pedersen(Google Inc.) Motivation: people was burdened with large online information Purpose: to help users find the information that are interesting to read Application: Google News [1]Personalized News Recommendation Based on Click Behavior
16. Click behavior advantage no ratings or negative votes after experiment (picture) news interests do change over time click distributions reflect the news trend different news trends in different locations news interests ↔ news trend in location (a certain extent) [1]How
17. Prediction User’s genuine interests The influence of local news trend Flow predicting user’s genuine news interest from a specific time period t combining predictions of past time periods predicting user’s current news interest recommendation [1]How(cont.)
18. [1]How(cont.) : predicting user’s current news interest : current news trend : past time user’s news interest Nt : all user’s clicks times in t time period G : the number of virtual clicks(smoothing factor)
19. Recommendation: (to rank a list of candidate articles) CR(article): content-based recommendation score CF(article): collaborative filtering recommendation score [1]How(cont.)
22. A Survey on Service Personalization 學生:張維辰 指導教授:劉立頌 時間:2010/09/10
23. Service Personalization Early research Overview of user-profile-based personalization User Profile Purpose Type Process of user-profile-based personalization Outline S.Gauch, M.Speretta, A. Chandramouli, and A. Micarelli, “User Profiles for Personalized Information Access, ” The Adaptive Web, LNCS 4321, pp.54-89
26. Purpose To record interest or habit of the user To filter out irrelevant information from the user To identify additional information of likely interest for the user User Profile
27. Type Static ex: name, age, country, education level Dynamic short-term long-term User Profile
28. Process 1.Collecting information about users user identification user information collection explicit implicit 2.User Profile Representations 3.User Profile Construction User Profile
29. User identification Software agents Logins Enhanced proxy servers Cookies Session ids Collecting information about users
31. Explicit Providing personal information (My Yahoo![110]) Rating (Web pages, Syskill&Webert[68];Movie, NetFlix[62];Consumer, ePinions[24]) Implicit Browsing history (OBIWAN [71]) Browsing activity ([71], Trajkova[99], Barrett[6]) All user activity (Seruku[83], Surfsaver[94]…) Search (Miserach[87], Liu[45]) User information collection
36. More abstract topics (not specific words or sets of related words) Concept profiles
37. User Profile Construction Building keyword profiles Building semantic network profiles Building concept profiles Thank you for attendance! Coming soon…
38.
39. A Survey on Service Personalization 學生:張維辰 指導教授:劉立頌 時間:2010/09/17
40. GediminasAdomavicius , Alexander Tuzhilin, Using Data Mining Methods to Build Customer Profiles, Computer, v.34 n.2, p.74-82, February 2001 (Journal) Building Customer Profiles by data mining methods
46. Key V=(W1, W2, W3, …, Wn) (待修改)Amalthaea’s Ecosystem[61](cont.) Web Pages Stemmer Html2txt filter Removal(commonly used) Html2url filter Hc x TF x IDF Moukas, A.: Amalthaea: Information Discovery And Filtering Using A Multi-agent Evolving Ecosystem. In: Applied Artificial Intelligence 11(5) (1997) 437-457 (Journal, Publisher : Taylor & Francis)
47. WebMate: A personal agent[13] Chen, L., Sycara, K.: A Personal Agent for Browsing and Searching. In: Proceedings of the 2nd International Conference on Autonomous Agents, Minneapolis/St. Paul, May 9-13, (1998) 132-139
48. Definition: 1. Profile set V = { V1, V2,…,VN} (N domains of interest for each user) 2. Document Di -> Vector Vi, i={1,…N} Vi={ e1,e2,…,eM}, ej =TF(wj, Di) x IDF(wj), j={1,…,M} WebMate[13](cont.)
49. Algorithm for multi TF-IDF vector learning: (待修改)WebMate[13](cont.) User marked “I like It” If |V| < N Add in set V T Parse HTML page F Compare every two vectors by (a) Extract TF-IDF vector Combine Vp, Vq with most similarity Vp = Vp + Vq Sort (a)
50. Widyantoro, D.H., Yin, J., El Nasr, M., Yang, L., Zacchi, A., Yen, J.: Alipes: A Swift Messenger In Cyberspace. In: Proc. 1999 AAAI Spring Symposium Workshop on Intelligent Agents in Cyberspace, Stanford, March 22-24 (1999)62-67 Alipes[103] Control
53. A Survey on Service Personalization 學生:張維辰 指導教授:劉立頌 時間:2010/10/22
54. Authors Susan Gauch, Jason Chaffee and Alexander Pretschner Motivation It’s impossible to use one approach to browsing or searching for every user according to preference. Purpose Personalized web browsing and search Application Web sites Ontology-based personalized search and browsing (Cited: 194 times)
55. Reference ontology: Concept, Source Concept To extract top levels of the subject hierarchies (already existing) Source associated web pages from Yahoo, Magellan, Lycos, and the Open Directory Project How-Browsing
64. A Survey on Text Categorization 學生:張維辰 指導教授:劉立頌 時間:2010/11/02
65. Classification supervised learning pre-defined categories ex. credit of consumer Clustering unsupervised learning unknown categories ex. similarity of consumer Preliminary
66. Motivation With the rapid growth of online information, it is difficult and time-consuming to deal with or classify the information by hand. Purpose To manage and use information easily Application Filter(personal portal site, email) Portal site Semantic identifier Image classification multimedia document classification Text Categorization(TC)
67. SVM(Support Vector Machine) Vapnik 1995 kNN(k-nearest neighbor) NB(Naïve Bayes) LLSF(Linear Least Squares Fit) NNet(Neural network) Approaches of TC