Formal Concept Analysis And Tag Recommendations In Collaborative Tagging Systems
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Formal Concept Analysis And Tag Recommendations In Collaborative Tagging Systems
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Author : Robert Jäschke
language : en
Publisher: Ios PressInc
Release Date : 2011-01-01
Formal Concept Analysis And Tag Recommendations In Collaborative Tagging Systems written by Robert Jäschke and has been published by Ios PressInc this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-01-01 with Computers categories.
One of the most noticeable innovation that emerged with the advent of the Web 2.0 and the focal point of this thesis are collaborative tagging systems. They allow users to annotate arbitrary resources with freely chosen keywords, so called tags. The tags
Recommender Systems For The Social Web
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Author : José J. Pazos Arias
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-01-24
Recommender Systems For The Social Web written by José J. Pazos Arias and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-01-24 with Technology & Engineering categories.
The recommendation of products, content and services cannot be considered newly born, although its widespread application is still in full swing. While its growing success in numerous sectors, the progress of the Social Web has revolutionized the architecture of participation and relationship in the Web, making it necessary to restate recommendation and reconciling it with Collaborative Tagging, as the popularization of authoring in the Web, and Social Networking, as the translation of personal relationships to the Web. Precisely, the convergence of recommendation with the above Social Web pillars is what motivates this book, which has collected contributions from well-known experts in the academy and the industry to provide a broader view of the problems that Social Recommenders might face with. If recommender systems have proven their key role in facilitating the user access to resources on the Web, when sharing resources has become social, it is natural for recommendation strategies in the Social Web era take into account the users’ point of view and the relationships among users to calculate their predictions. This book aims to help readers to discover and understand the interplay among legal issues such as privacy; technical aspects such as interoperability and scalability; and social aspects such as the influence of affinity, trust, reputation and likeness, when the goal is to offer recommendations that are truly useful to both the user and the provider.
Recommender Systems For Social Tagging Systems
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Author : Leandro Balby Marinho
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-02-10
Recommender Systems For Social Tagging Systems written by Leandro Balby Marinho and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-02-10 with Computers categories.
Social Tagging Systems are web applications in which users upload resources (e.g., bookmarks, videos, photos, etc.) and annotate it with a list of freely chosen keywords called tags. This is a grassroots approach to organize a site and help users to find the resources they are interested in. Social tagging systems are open and inherently social; features that have been proven to encourage participation. However, with the large popularity of these systems and the increasing amount of user-contributed content, information overload rapidly becomes an issue. Recommender Systems are well known applications for increasing the level of relevant content over the “noise” that continuously grows as more and more content becomes available online. In social tagging systems, however, we face new challenges. While in classic recommender systems the mode of recommendation is basically the resource, in social tagging systems there are three possible modes of recommendation: users, resources, or tags. Therefore suitable methods that properly exploit the different dimensions of social tagging systems data are needed. In this book, we survey the most recent and state-of-the-art work about a whole new generation of recommender systems built to serve social tagging systems. The book is divided into self-contained chapters covering the background material on social tagging systems and recommender systems to the more advanced techniques like the ones based on tensor factorization and graph-based models.
Open And Social Technologies For Networked Learning
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Author : Tobias Ley
language : en
Publisher: Springer
Release Date : 2013-04-18
Open And Social Technologies For Networked Learning written by Tobias Ley and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-04-18 with Education categories.
This volume constitutes the refereed post-proceedings of the IFIP WG 3.4 International Conference on Open and Social Technologies for Networked Learning, OST 2012, held in Tallinn, Estonia, in July/August 2012. The 16 full papers presented together with 3 short papers and 5 doctoral student papers were thoroughly reviewed and selected from numerous submissions. The papers cover a wide range of topics such as mobile learning, social networks, analytics and recommendations, workplace learning, learning analytics in higher education, collaborative learning in higher education, and managing open and social education.
Efficient Frequent Subtree Mining Beyond Forests
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Author : P. Welke
language : en
Publisher: IOS Press
Release Date : 2020-06-02
Efficient Frequent Subtree Mining Beyond Forests written by P. Welke and has been published by IOS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-02 with Computers categories.
A common paradigm in distance-based learning is to embed the instance space into a feature space equipped with a metric and define the dissimilarity between instances by the distance of their images in the feature space. Frequent connected subgraphs are sometimes used to define such feature spaces if the instances are graphs, but identifying the set of frequent connected subgraphs and subsequently computing embeddings for graph instances is computationally intractable. As a result, existing frequent subgraph mining algorithms either restrict the structural complexity of the instance graphs or require exponential delay between the output of subsequent patterns, meaning that distance-based learners lack an efficient way to operate on arbitrary graph data. This book presents a mining system that gives up the demand on the completeness of the pattern set, and instead guarantees a polynomial delay between subsequent patterns. To complement this, efficient methods devised to compute the embedding of arbitrary graphs into the Hamming space spanned by the pattern set are described. As a result, a system is proposed that allows the efficient application of distance-based learning methods to arbitrary graph databases. In addition to an introduction and conclusion, the book is divided into chapters covering: preliminaries; related work; probabilistic frequent subtrees; boosted probabilistic frequent subtrees; and fast computation, with a further two chapters on Hamiltonian path for cactus graphs and Poisson binomial distribution.
Knowledge Representation And Inductive Reasoning Using Conditional Logic And Sets Of Ranking Functions
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Author : S. Kutsch
language : en
Publisher: IOS Press
Release Date : 2021-02-09
Knowledge Representation And Inductive Reasoning Using Conditional Logic And Sets Of Ranking Functions written by S. Kutsch and has been published by IOS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-02-09 with Computers categories.
A core problem in Artificial Intelligence is the modeling of human reasoning. Classic-logical approaches are too rigid for this task, as deductive inference yielding logically correct results is not appropriate in situations where conclusions must be drawn based on the incomplete or uncertain knowledge present in virtually all real world scenarios. Since there are no mathematically precise and generally accepted definitions for the notions of plausible or rational, the question of what a knowledge base consisting of uncertain rules entails has long been an issue in the area of knowledge representation and reasoning. Different nonmonotonic logics and various semantic frameworks and axiom systems have been developed to address this question. The main theme of this book, Knowledge Representation and Inductive Reasoning using Conditional Logic and Sets of Ranking Functions, is inductive reasoning from conditional knowledge bases. Using ordinal conditional functions as ranking models for conditional knowledge bases, the author studies inferences induced by individual ranking models as well as by sets of ranking models. He elaborates in detail the interrelationships among the resulting inference relations and shows their formal properties with respect to established inference axioms. Based on the introduction of a novel classification scheme for conditionals, he also addresses the question of how to realize and implement the entailment relations obtained. In this work, “Steven Kutsch convincingly presents his ideas, provides illustrating examples for them, rigorously defines the introduced concepts, formally proves all technical results, and fully implements every newly introduced inference method in an advanced Java library (...). He significantly advances the state of the art in this field.” – Prof. Dr. Christoph Beierle of the FernUniversität in Hagen
Word Embeddings Reliability Semantic Change
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Author : J. Hellrich
language : en
Publisher: IOS Press
Release Date : 2019-08-08
Word Embeddings Reliability Semantic Change written by J. Hellrich and has been published by IOS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-08-08 with Computers categories.
Word embeddings are a form of distributional semantics increasingly popular for investigating lexical semantic change. However, typical training algorithms are probabilistic, limiting their reliability and the reproducibility of studies. Johannes Hellrich investigated this problem both empirically and theoretically and found some variants of SVD-based algorithms to be unaffected. Furthermore, he created the JeSemE website to make word embedding based diachronic research more accessible. It provides information on changes in word denotation and emotional connotation in five diachronic corpora. Finally, the author conducted two case studies on the applicability of these methods by investigating the historical understanding of electricity as well as words connected to Romanticism. They showed the high potential of distributional semantics for further applications in the digital humanities.
Shallow Discourse Parsing For German
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Author : P. Bourgonje
language : en
Publisher: IOS Press
Release Date : 2021-07-13
Shallow Discourse Parsing For German written by P. Bourgonje and has been published by IOS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07-13 with Computers categories.
The last few decades have seen impressive improvements in several areas of Natural Language Processing. Nevertheless, getting a computer to make sense of the discourse of utterances in a text remains challenging. Several different theories which aim to describe and analyze the coherent structure of a well-written text exist, but with varying degrees of applicability and feasibility for practical use. This book is about shallow discourse parsing, following the paradigm of the Penn Discourse TreeBank, a corpus containing over 1 million words annotated for discourse relations. When it comes to discourse processing, any language other than English must be considered a low-resource language. This book relates to discourse parsing for German. The limited availability of annotated data for German means that the potential of modern, deep-learning-based methods relying on such data is also limited. This book explores to what extent machine-learning and more recent deep-learning-based methods can be combined with traditional, linguistic feature engineering to improve performance for the discourse parsing task. The end-to-end shallow discourse parser for German developed for the purpose of this book is open-source and available online. Work has also been carried out on several connective lexicons in different languages. Strategies are discussed for creating or further developing such lexicons for a given language, as are suggestions on how to further increase their usefulness for shallow discourse parsing. The book will be of interest to all whose work involves Natural Language Processing, particularly in languages other than English.
Semantics Of Belief Change Operators For Intelligent Agents Iteration Postulates And Realizability
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Author : K. Sauerwald
language : en
Publisher: IOS Press
Release Date : 2022-11-03
Semantics Of Belief Change Operators For Intelligent Agents Iteration Postulates And Realizability written by K. Sauerwald and has been published by IOS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-03 with Computers categories.
One of the core problems in artificial intelligence is the modelling of human reasoning and intelligent behaviour. The representation of knowledge, and reasoning about it, are of crucial importance in achieving this. This book, Semantics of Belief Change Operators for Intelligent Agents: Iteration, Postulates, and Realizability, addresses a number of significant research questions in belief change theory from a semantic point of view; in particular, the connection between different types of belief changes and plausibility relations over possible worlds is investigated. This connection is characterized for revision over general classical logics, showing which relations are capturing AGM revision. In addition, those classical logics for which the correspondence between AGM revision and total preorders holds are precisely characterized. AGM revision in the Darwiche-Pearl framework for belief change over arbitrary sets of epistemic states is considered, demonstrating, especially, that for some sets of epistemic states, no AGM revision operator exists. A characterization of those sets of epistemic states for which AGM revision operators exist is presented. The expressive class of dynamic limited revision operators is introduced to provide revision operators for more sets of epistemic states. Specifications for the acceptance behaviour of various belief-change operators are examined, and those realizable by dynamic-limited revision operators are described. The iteration of AGM contraction in the Darwiche-Pearl framework is explored in detail, several known and novel iteration postulates for contraction are identified, and the relationships among these various postulates are determined. With a convincing presentation of ideas, the book refines and advances existing proposals of belief change, develops novel concepts and approaches, rigorously defines the concepts introduced, and formally proves all technical claims, propositions and theorems, significantly advancing the state-of-the-art in this field.
From Narratology To Computational Story Composition And Back
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Author : L. Berov
language : en
Publisher: IOS Press
Release Date : 2023-03-10
From Narratology To Computational Story Composition And Back written by L. Berov and has been published by IOS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-10 with Computers categories.
Although both deal with narratives, the two disciplines of Narrative Theory (NT) and Computational Story Composition (CSC) rarely exchange insights and ideas or engage in collaborative research. The former has its roots in the humanities, and attempts to analyze literary texts to derive an understanding of the concept of narrative. The latter is in the domain of Artificial Intelligence, and investigates the autonomous composition of fictional narratives in a way that could be deemed creative. The two disciplines employ different research methodologies at contradistinct levels of abstraction, making simultaneous research difficult, while a close exchange between the two disciplines would undoubtedly be desirable, not least because of the complementary approach to their object of study. This book, From Narratology to Computational Story Composition and Back, describes an exploratory study in generative modeling, a research methodology proposed to address the methodological differences between the two disciplines and allow for simultaneous NT and CSC research. It demonstrates how implementing narratological theories as computational, generative models can lead to insights for NT, and how grounding computational representations of narrative in NT can help CSC systems to take over creative responsibilities. It is the interplay of these two strands that underscores the feasibility and utility of generative modeling. The book is divided into 6 chapters: an introduction, followed by chapters on plot, fictional characters, plot quality estimation, and computational creativity, wrapped up by a conclusion. The book will be of interest to all those working in the fields of narrative theory and computational creativity.