The document presents an alignment-based approach to semi-supervised relation extraction that handles more than two arguments. The proposed method aims to improve both precision and coverage of relation extraction. It uses an alignment-based pattern matching approach and extracts all relationships with two or more arguments simultaneously to obtain high quality integrated results. Experimental results demonstrate the effectiveness of the method.
1. The document describes quantitative characterization of polymer-polymer and polymer-protein interactions using tracer sedimentation equilibrium.
2. The dependence of the thermodynamic activity coefficient on concentration was determined using two methods: power series expansion and scaled particle theory.
3. Results show BSA-BSA interactions are weaker than BSA-ficoll interactions, which are weaker than ficoll-ficoll interactions. Scaled particle theory modeling ficoll as a hard spherocylinder and BSA as a hard sphere described the experimental data well.
This document analyzes "A" players and their attributes at a store. It ranks two associates, with the top associate scoring highly in 7 attributes and metrics like MBE score, units per hour, and remakes. The document also lists 10 desirable associate attributes like being a team player, embracing initiatives, having a positive attitude, and attracting and developing top talent. Finally, it includes a recruiting action plan template to track associate availability and qualifications.
ICMI 2012 Workshop on gesture and speech productionLê Anh
In this slides, we present a common gesture speech framework for both virtual agents like ECA, IVA, VH and physical agents like humanoid robots. This framework is designed for different embodiments so that its processus are independent from a specific agent.
Context-aware similarities within the factorization framework (CaRR 2013 pres...Balázs Hidasi
This document summarizes research on incorporating context awareness into item-to-item recommendation similarities within a factorization framework. It describes four levels of context-aware similarity calculation and reports on experiments comparing the levels using four datasets. The results showed that context awareness generally improved recommendations but the degree of improvement depended heavily on the method and quality of the contextual information. The most context-sensitive method (elementwise product level 2) showed huge improvements or decreases depending on the context, while other methods showed only minor gains. Future work could explore different contexts, similarity measures, and evaluation approaches.
This document provides an introduction to Fourier series. It emphasizes conceptual understanding over mathematical rigor. It recommends that readers work through examples and derivations in the paper to fully understand Fourier series. The paper introduces Fourier series as representing periodic waveforms as sums of harmonically related sinusoids. It discusses Fourier coefficients and their physical interpretation. It also covers properties of Fourier series such as linearity, symmetry, time shifting, differentiation, and integration.
This document discusses point of view based clustering of socio-semantic networks. It describes how points of view can be created from semantic features of actors in a network to analyze the network from different perspectives. Semantic features include roles, names, relationships, and other attributes of actors. A point of view is defined as the set of all binary vectors representing each actor's features as defined by a subset of relevant features. The points of view allow influencing the network clustering process by using both structural and semantic information to extract non-evident information from various angles.
The Sigma Knowledge Engineering Environment is an IDE for developing large ontologies in first- and higher-order logic, such as the Suggested Upper Merged Ontology (SUMO). Sigma allows browsing ontologies, performing inference, and debugging. It provides tools for mapping, merging, translating between ontology languages, and consistency checking of knowledge bases.
Sequence learning under incidental conditions [poster]Fayme Yeates
The document reports on a study that investigated sequence learning under incidental conditions using a serial reaction time task. 64 participants were trained on one of two sequences without being told about the sequences. Those who learned the sequence that followed the rule "the current stimulus appears in the opposite location to the one two trials back" showed faster learning during training and better performance on a later test compared to those who learned the other sequence. Modeling with an augmented SRN neural network replicated the findings and provided support for associative learning accounts of incidental sequence learning.
1. The document describes quantitative characterization of polymer-polymer and polymer-protein interactions using tracer sedimentation equilibrium.
2. The dependence of the thermodynamic activity coefficient on concentration was determined using two methods: power series expansion and scaled particle theory.
3. Results show BSA-BSA interactions are weaker than BSA-ficoll interactions, which are weaker than ficoll-ficoll interactions. Scaled particle theory modeling ficoll as a hard spherocylinder and BSA as a hard sphere described the experimental data well.
This document analyzes "A" players and their attributes at a store. It ranks two associates, with the top associate scoring highly in 7 attributes and metrics like MBE score, units per hour, and remakes. The document also lists 10 desirable associate attributes like being a team player, embracing initiatives, having a positive attitude, and attracting and developing top talent. Finally, it includes a recruiting action plan template to track associate availability and qualifications.
ICMI 2012 Workshop on gesture and speech productionLê Anh
In this slides, we present a common gesture speech framework for both virtual agents like ECA, IVA, VH and physical agents like humanoid robots. This framework is designed for different embodiments so that its processus are independent from a specific agent.
Context-aware similarities within the factorization framework (CaRR 2013 pres...Balázs Hidasi
This document summarizes research on incorporating context awareness into item-to-item recommendation similarities within a factorization framework. It describes four levels of context-aware similarity calculation and reports on experiments comparing the levels using four datasets. The results showed that context awareness generally improved recommendations but the degree of improvement depended heavily on the method and quality of the contextual information. The most context-sensitive method (elementwise product level 2) showed huge improvements or decreases depending on the context, while other methods showed only minor gains. Future work could explore different contexts, similarity measures, and evaluation approaches.
This document provides an introduction to Fourier series. It emphasizes conceptual understanding over mathematical rigor. It recommends that readers work through examples and derivations in the paper to fully understand Fourier series. The paper introduces Fourier series as representing periodic waveforms as sums of harmonically related sinusoids. It discusses Fourier coefficients and their physical interpretation. It also covers properties of Fourier series such as linearity, symmetry, time shifting, differentiation, and integration.
This document discusses point of view based clustering of socio-semantic networks. It describes how points of view can be created from semantic features of actors in a network to analyze the network from different perspectives. Semantic features include roles, names, relationships, and other attributes of actors. A point of view is defined as the set of all binary vectors representing each actor's features as defined by a subset of relevant features. The points of view allow influencing the network clustering process by using both structural and semantic information to extract non-evident information from various angles.
The Sigma Knowledge Engineering Environment is an IDE for developing large ontologies in first- and higher-order logic, such as the Suggested Upper Merged Ontology (SUMO). Sigma allows browsing ontologies, performing inference, and debugging. It provides tools for mapping, merging, translating between ontology languages, and consistency checking of knowledge bases.
Sequence learning under incidental conditions [poster]Fayme Yeates
The document reports on a study that investigated sequence learning under incidental conditions using a serial reaction time task. 64 participants were trained on one of two sequences without being told about the sequences. Those who learned the sequence that followed the rule "the current stimulus appears in the opposite location to the one two trials back" showed faster learning during training and better performance on a later test compared to those who learned the other sequence. Modeling with an augmented SRN neural network replicated the findings and provided support for associative learning accounts of incidental sequence learning.
This document summarizes Chapter 2 of the textbook "Introduction to Analog & Digital Communications" which covers the Fourier representation of signals and systems. The chapter introduces the Fourier transform and its properties, such as how it relates the frequency and time domains. It also defines the Fourier transform mathematically and covers important concepts like the power spectral density and Dirichlet's conditions. Examples of applying the Fourier transform to common signals like rectangular and exponential pulses are also presented.
The document compares using LMO (E. coli bacteria) and LMO (Pichia pastoris yeast) to produce insulin and TMOFTM. E. coli is used to produce insulin by transforming it with genes for insulin subunits A and B, while Pichia pastoris is used to express the TMOFTM molecule. Both production methods involve a two-step LMO elimination process using heat and drying to kill the LMOs, verified by culture simulations showing no LMO presence.
An Investigation of Self-Interference Reduction Strategy in Correlated SM-OFD...Rosdiadee Nordin
1) The document presents a dynamic subcarrier allocation (DSA) scheme called DSA-ESINR that uses estimated signal-to-interference-plus-noise ratio (ESINR) as a metric to allocate subcarriers in a correlated space-division multiple access (SM-OFDMA) system.
2) Simulation results show that DSA-ESINR can minimize the effect of self-interference and improves subcarrier allocation as signal-to-noise ratio increases compared to a baseline DSA scheme.
3) Future work is proposed to study different correlation scenarios, apply adaptive modulation and coding, and analyze self-interference between space-time block coding and spatial multiplexing
This document summarizes a review of the Mekong Basin Futures Project. It outlines key issues facing the Mekong region including increasing population, economic development, climate change, fisheries and irrigation challenges, and upstream dam development. It cautions that while some changes can be influenced, historical forces and natural population growth will also drive significant change in the region. Humility and realism are important in assessing what the project and partners can impact.
[iGEM Workshop] Coming up with a Projectigemiitkgp
This document provides guidance for students developing a project for an iGEM competition. It recommends discussing project ideas with others, building on past iGEM work when possible, and allowing students to choose a project they find practical and interesting. The document also covers measurement and standardization, describing the BioBrick assembly standard and importance of using standardized parts to facilitate collaboration. Key steps in the assembly process are outlined.
Cosine modulated filter bank transmultiplexer using kaiser windowIAEME Publication
This document summarizes a research paper on designing a near perfect reconstruction cosine modulated filter-bank transmultiplexer using Kaiser window functions. It discusses using Kaiser windows with high side-lobe fall off rates to design prototype filters for analysis and synthesis sections. It also compares using an optimization algorithm versus no optimization to reduce inter-symbol interference and inter-carrier interference. The simulation results show the optimization approach provides less error compared to no optimization.
The Impact of Methods and Techniques on Outcomes from Agile Software Developm...David Parsons
This document analyzes a survey conducted by Scott Ambler in 2006 on agile software development. The authors performed additional statistical analysis on the raw data to determine: 1) If different numbers of agile methods used affects outcomes like productivity and quality, finding that using 1-2 methods is best. 2) Which individual methods and method pairs are most effective, finding XP and Scrum individually and combined are best. 3) Which agile techniques are most effective, finding test-driven design, pair programming and continuous integration help productivity and quality most. The analysis provides tentative conclusions but cautions that the data has limitations.
IOSR Journal of Electronics and Communication Engineering(IOSR-JECE) is an open access international journal that provides rapid publication (within a month) of articles in all areas of electronics and communication engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in electronics and communication engineering. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Sequential Labeling for Tracking Dynamic Dialog StatesSeokhwan Kim
1) The document discusses sequential labeling for tracking dynamic dialog states in conversations. It focuses on three dialog state tracking challenges: goals tracking, method tracking, and requested slots tracking.
2) The method presented uses conditional random fields (CRFs) with a BIO tagging scheme and sequential labeling to predict dialog states. Features include SLU hypotheses and system actions.
3) Experimental results on the DSTC 2 dataset show the CRF models outperform maximum entropy baselines on goals and method tracking in accuracy and error, and achieve comparable results to the baseline on requested slots tracking.
A Composite Kernel Approach for Dialog Topic Tracking with Structured Domain ...Seokhwan Kim
A Composite Kernel Approach for Dialog Topic Tracking with Structured Domain Knowledge from Wikipedia.
Seokhwan Kim, Rafael E. Banchs, Haizhou Li.
The 52nd Annual Meeting of the Association for Computational Linguistics (ACL 2014), Baltimore, Jun 2014
An Alignment-based Pattern Representation Model for Information ExtractionSeokhwan Kim
This document proposes an alignment-based pattern representation model for information extraction that uses both lexical sequences and dependency analysis features. It describes previous syntax-dependent models and introduces an approach based on lexical alignment of arguments that considers dependency analysis as an additional feature. An evaluation on a scenario template task shows the proposed model outperforms previous syntax-dependent models in precision, recall, and F-measure.
Towards Improving Dialogue Topic Tracking Performances with Wikification of C...Seokhwan Kim
This document proposes improving dialogue topic tracking by linking concept mentions in spoken dialogues to relevant Wikipedia entries through a process called wikification. It presents a method for wikifying mentions by ranking candidate Wikipedia concepts and adding wikification-based features to existing topic tracking models. An experiment on tourism dialogues found the additional wikification features improved accuracy, achieving up to 79.12% for topic prediction and 50.10% for transition detection.
Wikipedia-based Kernels for Dialogue Topic TrackingSeokhwan Kim
This document presents a Wikipedia-based kernel method for dialogue topic tracking. It aims to incorporate various types of knowledge from Wikipedia to improve topic tracking, without requiring significant effort to build domain-specific resources. An evaluation on a dialogue corpus shows the proposed approach outperforms baselines in segmenting dialogues into coherent topic segments and identifying topic transitions, especially for system-initiative cases. Ongoing work involves using additional Wikipedia knowledge and presenting results at ACL 2014.
Natural Language in Human-Robot InteractionSeokhwan Kim
The document provides an overview of natural language in human-robot interaction. It discusses how natural language and speech are important for enabling complex tasks and collaborative work between humans and robots. Developing robots that can understand and generate natural language requires techniques from various fields including linguistics, computer science, psychology and more. Human-robot interaction poses unique challenges compared to human-human interaction, as robots have limitations in intelligence, multimodal capabilities and how "human-like" they can behave.
AI-powered Chatbots - what they are and where they're goingKeith Klundt
This document discusses the rise of chatbots and conversational commerce. It notes that messaging apps have become very popular and chatbots provide a way for companies to engage customers in these spaces. The document outlines the history of chatbots in 2016 and discusses how technologies like artificial intelligence and machine learning will allow chatbots to have more natural language conversations. It also notes analysts' predictions that the market for chatbots and virtual assistants will grow significantly in coming years.
Este documento describe los requisitos para elaborar una misión y visión efectivas para una organización. Explica que la misión debe definir el propósito básico, los sectores y usuarios objetivos, y los productos y servicios. La visión debe ser medible, atractiva, posible, estratégica, entendible e inspiradora. Ambas deben elaborarse con la participación de un equipo que represente a la organización y deben revisarse periódicamente.
Deep Recurrent Neural Networks with Layer-wise Multi-head Attentions for Punc...Seokhwan Kim
The document describes a deep recurrent neural network model with multi-head attention mechanisms for punctuation restoration. The model stacks multiple bidirectional recurrent layers to encode context and applies multi-head attention to each layer to capture hierarchical features. Evaluated on an English speech transcription dataset, the proposed model outperforms previous methods that use convolutional or recurrent neural networks alone or with single-head attention.
Dynamic Memory Networks for Dialogue Topic TrackingSeokhwan Kim
The document proposes using a Dynamic Memory Network (DMN) model for dialogue topic tracking. It summarizes baseline CNN and RCNN models, then describes the DMN model which represents dialogue state as memory slots updated through utterances using gating mechanisms. It evaluates the models on a dialogue corpus, finding the DMN with cross-slot interactions outperforms baselines with the highest F1 score of 0.7049 and lower segmentation errors.
The Fifth Dialog State Tracking Challenge (DSTC5)Seokhwan Kim
The Fifth Dialog State Tracking Challenge (DSTC5) focused on adapting dialog state tracking models to a new language (Chinese) using datasets of human-human dialogs about tourist information in English and Chinese. It featured main tasks of dialog state tracking and pilot tasks of spoken language understanding, speech act prediction, and spoken language generation. The document outlines the datasets, tasks, baselines and evaluation metrics for each task and reports results from participating systems.
Exploring Convolutional and Recurrent Neural Networks in Sequential Labelling...Seokhwan Kim
The document describes research into using convolutional and recurrent neural networks for dialogue topic tracking. It presents three models: (1) a convolutional neural network that represents utterances as matrices of word embeddings and uses convolutional filters, (2) a recurrent neural network that connects utterance embeddings in a window over time, and (3) a recurrent convolutional network that combines the CNN and RNN architectures. The models are evaluated on a dialogue corpus annotated with topic categories, with the recurrent convolutional network achieving the best performance.
This document summarizes Chapter 2 of the textbook "Introduction to Analog & Digital Communications" which covers the Fourier representation of signals and systems. The chapter introduces the Fourier transform and its properties, such as how it relates the frequency and time domains. It also defines the Fourier transform mathematically and covers important concepts like the power spectral density and Dirichlet's conditions. Examples of applying the Fourier transform to common signals like rectangular and exponential pulses are also presented.
The document compares using LMO (E. coli bacteria) and LMO (Pichia pastoris yeast) to produce insulin and TMOFTM. E. coli is used to produce insulin by transforming it with genes for insulin subunits A and B, while Pichia pastoris is used to express the TMOFTM molecule. Both production methods involve a two-step LMO elimination process using heat and drying to kill the LMOs, verified by culture simulations showing no LMO presence.
An Investigation of Self-Interference Reduction Strategy in Correlated SM-OFD...Rosdiadee Nordin
1) The document presents a dynamic subcarrier allocation (DSA) scheme called DSA-ESINR that uses estimated signal-to-interference-plus-noise ratio (ESINR) as a metric to allocate subcarriers in a correlated space-division multiple access (SM-OFDMA) system.
2) Simulation results show that DSA-ESINR can minimize the effect of self-interference and improves subcarrier allocation as signal-to-noise ratio increases compared to a baseline DSA scheme.
3) Future work is proposed to study different correlation scenarios, apply adaptive modulation and coding, and analyze self-interference between space-time block coding and spatial multiplexing
This document summarizes a review of the Mekong Basin Futures Project. It outlines key issues facing the Mekong region including increasing population, economic development, climate change, fisheries and irrigation challenges, and upstream dam development. It cautions that while some changes can be influenced, historical forces and natural population growth will also drive significant change in the region. Humility and realism are important in assessing what the project and partners can impact.
[iGEM Workshop] Coming up with a Projectigemiitkgp
This document provides guidance for students developing a project for an iGEM competition. It recommends discussing project ideas with others, building on past iGEM work when possible, and allowing students to choose a project they find practical and interesting. The document also covers measurement and standardization, describing the BioBrick assembly standard and importance of using standardized parts to facilitate collaboration. Key steps in the assembly process are outlined.
Cosine modulated filter bank transmultiplexer using kaiser windowIAEME Publication
This document summarizes a research paper on designing a near perfect reconstruction cosine modulated filter-bank transmultiplexer using Kaiser window functions. It discusses using Kaiser windows with high side-lobe fall off rates to design prototype filters for analysis and synthesis sections. It also compares using an optimization algorithm versus no optimization to reduce inter-symbol interference and inter-carrier interference. The simulation results show the optimization approach provides less error compared to no optimization.
The Impact of Methods and Techniques on Outcomes from Agile Software Developm...David Parsons
This document analyzes a survey conducted by Scott Ambler in 2006 on agile software development. The authors performed additional statistical analysis on the raw data to determine: 1) If different numbers of agile methods used affects outcomes like productivity and quality, finding that using 1-2 methods is best. 2) Which individual methods and method pairs are most effective, finding XP and Scrum individually and combined are best. 3) Which agile techniques are most effective, finding test-driven design, pair programming and continuous integration help productivity and quality most. The analysis provides tentative conclusions but cautions that the data has limitations.
IOSR Journal of Electronics and Communication Engineering(IOSR-JECE) is an open access international journal that provides rapid publication (within a month) of articles in all areas of electronics and communication engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in electronics and communication engineering. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Sequential Labeling for Tracking Dynamic Dialog StatesSeokhwan Kim
1) The document discusses sequential labeling for tracking dynamic dialog states in conversations. It focuses on three dialog state tracking challenges: goals tracking, method tracking, and requested slots tracking.
2) The method presented uses conditional random fields (CRFs) with a BIO tagging scheme and sequential labeling to predict dialog states. Features include SLU hypotheses and system actions.
3) Experimental results on the DSTC 2 dataset show the CRF models outperform maximum entropy baselines on goals and method tracking in accuracy and error, and achieve comparable results to the baseline on requested slots tracking.
A Composite Kernel Approach for Dialog Topic Tracking with Structured Domain ...Seokhwan Kim
A Composite Kernel Approach for Dialog Topic Tracking with Structured Domain Knowledge from Wikipedia.
Seokhwan Kim, Rafael E. Banchs, Haizhou Li.
The 52nd Annual Meeting of the Association for Computational Linguistics (ACL 2014), Baltimore, Jun 2014
An Alignment-based Pattern Representation Model for Information ExtractionSeokhwan Kim
This document proposes an alignment-based pattern representation model for information extraction that uses both lexical sequences and dependency analysis features. It describes previous syntax-dependent models and introduces an approach based on lexical alignment of arguments that considers dependency analysis as an additional feature. An evaluation on a scenario template task shows the proposed model outperforms previous syntax-dependent models in precision, recall, and F-measure.
Towards Improving Dialogue Topic Tracking Performances with Wikification of C...Seokhwan Kim
This document proposes improving dialogue topic tracking by linking concept mentions in spoken dialogues to relevant Wikipedia entries through a process called wikification. It presents a method for wikifying mentions by ranking candidate Wikipedia concepts and adding wikification-based features to existing topic tracking models. An experiment on tourism dialogues found the additional wikification features improved accuracy, achieving up to 79.12% for topic prediction and 50.10% for transition detection.
Wikipedia-based Kernels for Dialogue Topic TrackingSeokhwan Kim
This document presents a Wikipedia-based kernel method for dialogue topic tracking. It aims to incorporate various types of knowledge from Wikipedia to improve topic tracking, without requiring significant effort to build domain-specific resources. An evaluation on a dialogue corpus shows the proposed approach outperforms baselines in segmenting dialogues into coherent topic segments and identifying topic transitions, especially for system-initiative cases. Ongoing work involves using additional Wikipedia knowledge and presenting results at ACL 2014.
Natural Language in Human-Robot InteractionSeokhwan Kim
The document provides an overview of natural language in human-robot interaction. It discusses how natural language and speech are important for enabling complex tasks and collaborative work between humans and robots. Developing robots that can understand and generate natural language requires techniques from various fields including linguistics, computer science, psychology and more. Human-robot interaction poses unique challenges compared to human-human interaction, as robots have limitations in intelligence, multimodal capabilities and how "human-like" they can behave.
AI-powered Chatbots - what they are and where they're goingKeith Klundt
This document discusses the rise of chatbots and conversational commerce. It notes that messaging apps have become very popular and chatbots provide a way for companies to engage customers in these spaces. The document outlines the history of chatbots in 2016 and discusses how technologies like artificial intelligence and machine learning will allow chatbots to have more natural language conversations. It also notes analysts' predictions that the market for chatbots and virtual assistants will grow significantly in coming years.
Este documento describe los requisitos para elaborar una misión y visión efectivas para una organización. Explica que la misión debe definir el propósito básico, los sectores y usuarios objetivos, y los productos y servicios. La visión debe ser medible, atractiva, posible, estratégica, entendible e inspiradora. Ambas deben elaborarse con la participación de un equipo que represente a la organización y deben revisarse periódicamente.
Deep Recurrent Neural Networks with Layer-wise Multi-head Attentions for Punc...Seokhwan Kim
The document describes a deep recurrent neural network model with multi-head attention mechanisms for punctuation restoration. The model stacks multiple bidirectional recurrent layers to encode context and applies multi-head attention to each layer to capture hierarchical features. Evaluated on an English speech transcription dataset, the proposed model outperforms previous methods that use convolutional or recurrent neural networks alone or with single-head attention.
Dynamic Memory Networks for Dialogue Topic TrackingSeokhwan Kim
The document proposes using a Dynamic Memory Network (DMN) model for dialogue topic tracking. It summarizes baseline CNN and RCNN models, then describes the DMN model which represents dialogue state as memory slots updated through utterances using gating mechanisms. It evaluates the models on a dialogue corpus, finding the DMN with cross-slot interactions outperforms baselines with the highest F1 score of 0.7049 and lower segmentation errors.
The Fifth Dialog State Tracking Challenge (DSTC5)Seokhwan Kim
The Fifth Dialog State Tracking Challenge (DSTC5) focused on adapting dialog state tracking models to a new language (Chinese) using datasets of human-human dialogs about tourist information in English and Chinese. It featured main tasks of dialog state tracking and pilot tasks of spoken language understanding, speech act prediction, and spoken language generation. The document outlines the datasets, tasks, baselines and evaluation metrics for each task and reports results from participating systems.
Exploring Convolutional and Recurrent Neural Networks in Sequential Labelling...Seokhwan Kim
The document describes research into using convolutional and recurrent neural networks for dialogue topic tracking. It presents three models: (1) a convolutional neural network that represents utterances as matrices of word embeddings and uses convolutional filters, (2) a recurrent neural network that connects utterance embeddings in a window over time, and (3) a recurrent convolutional network that combines the CNN and RNN architectures. The models are evaluated on a dialogue corpus annotated with topic categories, with the recurrent convolutional network achieving the best performance.
The Fourth Dialog State Tracking Challenge (DSTC4)Seokhwan Kim
The document summarizes the Fourth Dialog State Tracking Challenge (DSTC4) held at IWSDS 2016. It provides an overview of the main task, which involved dialogue state tracking on a dataset of tourist information dialogues in Singapore. Participants were asked to estimate dialogue states across turns to track topics, slots, and values. The challenge evaluated submissions using frame accuracy and slot-based metrics. Ensemble methods that combined top-performing systems, such as majority voting of the top 3 entries, achieved the best results.
Wikification of Concept Mentions within Spoken Dialogues Using Domain Constra...Seokhwan Kim
This paper presents an approach to link concept mentions in spoken dialogue transcripts to relevant concepts in Wikipedia, consisting of three steps: (1) analyzing properties of each mention, (2) generating candidate concepts based on the analysis, and (3) ranking candidates using a learning model. The approach is evaluated on tourist guide dialogues and shows improved performance over baselines that do not apply constraints from mention analysis or Wikipedia.
A Graph-based Cross-lingual Projection Approach for Spoken Language Understan...Seokhwan Kim
This paper proposes a graph-based projection approach to improve the robustness of cross-lingual spoken language understanding (SLU) when applied to a new language. The approach constructs graphs using trigrams in the dataset connected by word alignments and semantic similarities. It then performs label propagation to induce labels for unlabeled nodes. An evaluation on English-Korean SLU tasks shows the graph-based projection approach improves over direct projection and training only on the source language data, achieving higher precision, recall and accuracy for named entity recognition and dialog act identification.
A Graph-based Cross-lingual Projection Approach for Weakly Supervised Relatio...Seokhwan Kim
This document describes a graph-based approach for cross-lingual projection of relation annotations from English to Korean. The approach constructs a graph with nodes for entity pairs and context words, connected by edges representing similarity. Label propagation is used to transfer annotations across the graph. Evaluation on four relations shows the graph-based approach improves over direct projection and other self-supervised methods, achieving a top F-measure of 76.3%. The approach helps alleviate errors from direct projection while leveraging contextual information.
A semi-supervised method for efficient construction of statistical spoken lan...Seokhwan Kim
This document presents a semi-supervised framework to efficiently construct statistical spoken language understanding resources with low cost. It generates context patterns from a small set of seed entities and unlabeled utterances. These patterns are used to extract new entities by aligning utterances and replacing entity labels. Extracted entities above a score threshold are added back to the seed set, repeating the process. An evaluation on a corpus achieved high precision and recall in extracting city names, months, and day numbers with this method.
A spoken dialog system for electronic program guide information accessSeokhwan Kim
This paper presents POSSDS-EPG, a spoken dialogue system for accessing electronic program guide (EPG) information. It consists of modules for automatic speech recognition, spoken language understanding, dialogue management, system utterance generation, text-to-speech synthesis, and an EPG database manager. The EPG database manager automatically extracts and builds a content database from popular EPG websites to reflect up-to-date program information. This database is then used by other modules to build their resources. Evaluations showed the system performs EPG tasks with high performance and can be managed with low cost.
A Cross-Lingual Annotation Projection Approach for Relation DetectionSeokhwan Kim
This document describes a method for cross-lingual annotation projection to detect relations in a target language without extensive annotation efforts. It projects relation annotations from a source language to a target language using word alignments from a parallel corpus. It introduces strategies to reduce noise from the projection process, including alignment filtering based on heuristics, alignment correction using a bilingual dictionary, and instance selection based on relation detection confidence scores. The method is evaluated on projecting relation annotations from English to Korean sentences.
A Cross-lingual Annotation Projection-based Self-supervision Approach for Ope...Seokhwan Kim
The document proposes a self-supervised approach for open information extraction without human annotation. It leverages cross-lingual annotation projection using parallel corpora, projecting annotations from a source language with resources to a target language. Annotations are obtained on the source language by identifying entity pairs and extracting relationships. These annotations are then projected to the target language using word alignments, generating training examples without human supervision.
Prescriptive analytics BA4206 Anna University PPTFreelance
Business analysis - Prescriptive analytics Introduction to Prescriptive analytics
Prescriptive Modeling
Non Linear Optimization
Demonstrating Business Performance Improvement
Unlocking WhatsApp Marketing with HubSpot: Integrating Messaging into Your Ma...Niswey
50 million companies worldwide leverage WhatsApp as a key marketing channel. You may have considered adding it to your marketing mix, or probably already driving impressive conversions with WhatsApp.
But wait. What happens when you fully integrate your WhatsApp campaigns with HubSpot?
That's exactly what we explored in this session.
We take a look at everything that you need to know in order to deploy effective WhatsApp marketing strategies, and integrate it with your buyer journey in HubSpot. From technical requirements to innovative campaign strategies, to advanced campaign reporting - we discuss all that and more, to leverage WhatsApp for maximum impact. Check out more details about the event here https://events.hubspot.com/events/details/hubspot-new-delhi-presents-unlocking-whatsapp-marketing-with-hubspot-integrating-messaging-into-your-marketing-strategy/
The Most Inspiring Entrepreneurs to Follow in 2024.pdfthesiliconleaders
In a world where the potential of youth innovation remains vastly untouched, there emerges a guiding light in the form of Norm Goldstein, the Founder and CEO of EduNetwork Partners. His dedication to this cause has earned him recognition as a Congressional Leadership Award recipient.
AI Transformation Playbook: Thinking AI-First for Your BusinessArijit Dutta
I dive into how businesses can stay competitive by integrating AI into their core processes. From identifying the right approach to building collaborative teams and recognizing common pitfalls, this guide has got you covered. AI transformation is a journey, and this playbook is here to help you navigate it successfully.
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Profiles of Iconic Fashion Personalities.pdfTTop Threads
The fashion industry is dynamic and ever-changing, continuously sculpted by trailblazing visionaries who challenge norms and redefine beauty. This document delves into the profiles of some of the most iconic fashion personalities whose impact has left a lasting impression on the industry. From timeless designers to modern-day influencers, each individual has uniquely woven their thread into the rich fabric of fashion history, contributing to its ongoing evolution.
The report *State of D2C in India: A Logistics Update* talks about the evolving dynamics of the d2C landscape with a particular focus on how brands navigate the complexities of logistics. Third Party Logistics enablers emerge indispensable partners in facilitating the growth journey of D2C brands, offering cost-effective solutions tailored to their specific needs. As D2C brands continue to expand, they encounter heightened operational complexities with logistics standing out as a significant challenge. Logistics not only represents a substantial cost component for the brands but also directly influences the customer experience. Establishing efficient logistics operations while keeping costs low is therefore a crucial objective for brands. The report highlights how 3PLs are meeting the rising demands of D2C brands, supporting their expansion both online and offline, and paving the way for sustainable, scalable growth in this fast-paced market.
[To download this presentation, visit:
https://www.oeconsulting.com.sg/training-presentations]
This presentation is a curated compilation of PowerPoint diagrams and templates designed to illustrate 20 different digital transformation frameworks and models. These frameworks are based on recent industry trends and best practices, ensuring that the content remains relevant and up-to-date.
Key highlights include Microsoft's Digital Transformation Framework, which focuses on driving innovation and efficiency, and McKinsey's Ten Guiding Principles, which provide strategic insights for successful digital transformation. Additionally, Forrester's framework emphasizes enhancing customer experiences and modernizing IT infrastructure, while IDC's MaturityScape helps assess and develop organizational digital maturity. MIT's framework explores cutting-edge strategies for achieving digital success.
These materials are perfect for enhancing your business or classroom presentations, offering visual aids to supplement your insights. Please note that while comprehensive, these slides are intended as supplementary resources and may not be complete for standalone instructional purposes.
Frameworks/Models included:
Microsoft’s Digital Transformation Framework
McKinsey’s Ten Guiding Principles of Digital Transformation
Forrester’s Digital Transformation Framework
IDC’s Digital Transformation MaturityScape
MIT’s Digital Transformation Framework
Gartner’s Digital Transformation Framework
Accenture’s Digital Strategy & Enterprise Frameworks
Deloitte’s Digital Industrial Transformation Framework
Capgemini’s Digital Transformation Framework
PwC’s Digital Transformation Framework
Cisco’s Digital Transformation Framework
Cognizant’s Digital Transformation Framework
DXC Technology’s Digital Transformation Framework
The BCG Strategy Palette
McKinsey’s Digital Transformation Framework
Digital Transformation Compass
Four Levels of Digital Maturity
Design Thinking Framework
Business Model Canvas
Customer Journey Map
Tired of chasing down expiring contracts and drowning in paperwork? Mastering contract management can significantly enhance your business efficiency and productivity. This guide unveils expert secrets to streamline your contract management process. Learn how to save time, minimize risk, and achieve effortless contract management.
During the budget session of 2024-25, the finance minister, Nirmala Sitharaman, introduced the “solar Rooftop scheme,” also known as “PM Surya Ghar Muft Bijli Yojana.” It is a subsidy offered to those who wish to put up solar panels in their homes using domestic power systems. Additionally, adopting photovoltaic technology at home allows you to lower your monthly electricity expenses. Today in this blog we will talk all about what is the PM Surya Ghar Muft Bijli Yojana. How does it work? Who is eligible for this yojana and all the other things related to this scheme?
An alignment-based approach to semi-supervised relation extraction including multiple arguments
1. An alignment-based Approach to Semi-supervised Relation Extraction
Including Multiple Arguments
Seokhwan Kim, Minwoo Jeong, Gary Geunbae Lee, Kwangil Ko, and Zino Lee
{megaup, stardust, gblee}@postech.ac.kr, {kik, zino}@alticast.com
Abstract - We present an alignment-based approach to semi-supervised relation extraction task including more than two arguments. We concentrate
on improving not only the precision of the extracted result, but also on the coverage of the method. Our relation extraction method is based on an
alignment-based pattern matching approach which provides more flexibility of the method. In addition, we extract all relationships including two or
more arguments at once in order to obtain the integrated result with high quality. We present experimental results which indicate the effectiveness of
our method.
Alignment-based Information Extraction
v Information Extraction v Sentence Alignment for Information Extraction w Matrix Computation
w Extracting the defined number of relevant w Example M i 1, j 1 sim i
arguments from natural language documents the character <ROLE> portrayed by <ACTOR> in the television series <PROGRAM> is
1, j 1
M i 1, j gp
w Subtasks M i, j max
M i , j 1 gp
# of arguments subtask 0
1 named-entity recognition character Michael Scofield portrayed by Wentworth Miller in the TV series Prison Break is
{
1, if PTNi = RAWj
2 binary relation extraction w Alignment Matrix
simi,j = or PTNi = <label>
more than 2 relation/event extraction character
the character Michael Scofield portrayed by Wentworth Miller in the TV series Prison Break is
0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0, otherwise
<ROLE> 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2
w Approaches portrayed
by
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w Trace Back
<ACTOR> 1 2 2 3 3 4 5 5 5 5 5 5 5 5 5
w Supervised in
the
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M i,j next position
w Un/Semi-Supervised television
series
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8 M i,j-1 +gp [i, j-1]
M i-1,j-1 + simi,j [i-1, j-1]
<PROGRAM> 1 2 3 3 4 4 5 6 6 7 8 8 9 9 9
is 1 2 3 3 4 4 5 6 6 7 8 8 9 9 10
M i-1,j +gp [i-1, j]
Semi-supervised Relation Extraction Including Multiple Arguments
v Overall Architecture v Context Patterns Extraction v Alignment-based Verification
1) Searching the sentences containing all w Aligning between two candidate arguments
arguments of each tuple in source documents
Seed Data
2) Segmenting out subpart of the sentence with max{M(A, B)}× 2
n arguments
similarity(A,B) =
the window size w length(A) + length(B)
3) Replacing the parts of arguments in the sub-
Seed Data Seed Data Seed Data Seed Data Seed Data Seed Data Seed Data
w Tuple clustering based on
2 arguments k arguments n args
sentence with argument labels
Extracting Extracting
… Extracting
… Extracting Extracting
… Extracting
… Extracting
v Relation Extraction based on sim(tuple1, tuple2) =
Context Context Context Context Context Context Context
Patterns Patterns Patterns Patterns Patterns Patterns Patterns
Relation Relation Relation Relation Relation Relation Relation
Pairwise Alignment |args|
tuple2i)
i=1 similarity(tuple1i,
Extraction Extraction Extraction Extraction Extraction Extraction Extraction
w Alignment score
|arguments|
Validation & max{M(PTN, RAW)}
Integration
Results
score(PTN, RAW) = w Selecting the most probable tuple for each
n arguments
length(PTN)
cluster
Experimental Results
v Experimental Setup
w 930 Korean news documents (13,175 sents) about TV series
w Only a tuple with 4 arguments (CHANNEL, PROGRAM, ACTOR, ROLE) is used as a seed
v Comparison on the Coverage for
w Each result is collected after the first iteration and evaluated manually
Various Threshold Values
v Result of the verification v Result of the integration
90
80
before after with only
type of with all
70
verification verification type of binary
relations intermediates 60
|tuples| P |tuples| P relations relations
# of correct results
(A,R) 249 36.55 79 73.42 |tuples| P |tuples| P
50
(P,R) 19 52.63 17 58.82 (P,A,R) 9 77.78 9 88.89 40
(P,A) 10 60 10 60 (C,P,R) 11 81.82 16 87.5 30
(C,P) 12 33.33 6 66.67 (C,P,A) 12 58.33 9 77.78 20
(P,A,R) 7 42.86 5 60 (C,P,A,R) 8 87.5 16 87.5 including 2 arguments
(C,P,R) 18 55.56 16 81.25 10 including 3 arguments
including 4 arguments
(C,P,A) 8 62.5 8 75 w th = 0.85 0
1.00 0.95 0.90 0.85 0.80 0.75 0.70
(C,P,A,R) 15 60 14 85.71 w C(Channel), P(Program), A(Actor), R(Role) threshold