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  1. Huo, W.: Automatic multi-word term extraction and its application to Web-page summarization (2012) 0.68
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    Abstract
    In this thesis we propose three new word association measures for multi-word term extraction. We combine these association measures with LocalMaxs algorithm in our extraction model and compare the results of different multi-word term extraction methods. Our approach is language and domain independent and requires no training data. It can be applied to such tasks as text summarization, information retrieval, and document classification. We further explore the potential of using multi-word terms as an effective representation for general web-page summarization. We extract multi-word terms from human written summaries in a large collection of web-pages, and generate the summaries by aligning document words with these multi-word terms. Our system applies machine translation technology to learn the aligning process from a training set and focuses on selecting high quality multi-word terms from human written summaries to generate suitable results for web-page summarization.
    Content
    A Thesis presented to The University of Guelph In partial fulfilment of requirements for the degree of Master of Science in Computer Science. Vgl. Unter: http://www.inf.ufrgs.br%2F~ceramisch%2Fdownload_files%2Fpublications%2F2009%2Fp01.pdf.
    Date
    10. 1.2013 19:22:47
  2. Kleineberg, M.: Context analysis and context indexing : formal pragmatics in knowledge organization (2014) 0.61
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    Source
    http://www.google.de/url?sa=t&rct=j&q=&esrc=s&source=web&cd=5&ved=0CDQQFjAE&url=http%3A%2F%2Fdigbib.ubka.uni-karlsruhe.de%2Fvolltexte%2Fdocuments%2F3131107&ei=HzFWVYvGMsiNsgGTyoFI&usg=AFQjCNE2FHUeR9oQTQlNC4TPedv4Mo3DaQ&sig2=Rlzpr7a3BLZZkqZCXXN_IA&bvm=bv.93564037,d.bGg&cad=rja
  3. Li, L.; Shang, Y.; Zhang, W.: Improvement of HITS-based algorithms on Web documents 0.51
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    Content
    Vgl.: http%3A%2F%2Fdelab.csd.auth.gr%2F~dimitris%2Fcourses%2Fir_spring06%2Fpage_rank_computing%2Fp527-li.pdf. Vgl. auch: http://www2002.org/CDROM/refereed/643/.
    Source
    WWW '02: Proceedings of the 11th International Conference on World Wide Web, May 7-11, 2002, Honolulu, Hawaii, USA
  4. Zeng, Q.; Yu, M.; Yu, W.; Xiong, J.; Shi, Y.; Jiang, M.: Faceted hierarchy : a new graph type to organize scientific concepts and a construction method (2019) 0.46
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    Abstract
    On a scientific concept hierarchy, a parent concept may have a few attributes, each of which has multiple values being a group of child concepts. We call these attributes facets: classification has a few facets such as application (e.g., face recognition), model (e.g., svm, knn), and metric (e.g., precision). In this work, we aim at building faceted concept hierarchies from scientific literature. Hierarchy construction methods heavily rely on hypernym detection, however, the faceted relations are parent-to-child links but the hypernym relation is a multi-hop, i.e., ancestor-to-descendent link with a specific facet "type-of". We use information extraction techniques to find synonyms, sibling concepts, and ancestor-descendent relations from a data science corpus. And we propose a hierarchy growth algorithm to infer the parent-child links from the three types of relationships. It resolves conflicts by maintaining the acyclic structure of a hierarchy.
    Content
    Vgl.: https%3A%2F%2Faclanthology.org%2FD19-5317.pdf&usg=AOvVaw0ZZFyq5wWTtNTvNkrvjlGA.
  5. Hotho, A.; Bloehdorn, S.: Data Mining 2004 : Text classification by boosting weak learners based on terms and concepts (2004) 0.44
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    Content
    Vgl.: http://www.google.de/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&cad=rja&ved=0CEAQFjAA&url=http%3A%2F%2Fciteseerx.ist.psu.edu%2Fviewdoc%2Fdownload%3Fdoi%3D10.1.1.91.4940%26rep%3Drep1%26type%3Dpdf&ei=dOXrUMeIDYHDtQahsIGACg&usg=AFQjCNHFWVh6gNPvnOrOS9R3rkrXCNVD-A&sig2=5I2F5evRfMnsttSgFF9g7Q&bvm=bv.1357316858,d.Yms.
    Date
    8. 1.2013 10:22:32
  6. Mas, S.; Marleau, Y.: Proposition of a faceted classification model to support corporate information organization and digital records management (2009) 0.43
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    Abstract
    The employees of an organization often use a personal hierarchical classification scheme to organize digital documents that are stored on their own workstations. As this may make it hard for other employees to retrieve these documents, there is a risk that the organization will lose track of needed documentation. Furthermore, the inherent boundaries of such a hierarchical structure require making arbitrary decisions about which specific criteria the classification will b.e based on (for instance, the administrative activity or the document type, although a document can have several attributes and require classification in several classes).A faceted classification model to support corporate information organization is proposed. Partially based on Ranganathan's facets theory, this model aims not only to standardize the organization of digital documents, but also to simplify the management of a document throughout its life cycle for both individuals and organizations, while ensuring compliance to regulatory and policy requirements.
    Footnote
    Vgl.: http://ieeexplore.ieee.org/Xplore/login.jsp?reload=true&url=http%3A%2F%2Fieeexplore.ieee.org%2Fiel5%2F4755313%2F4755314%2F04755480.pdf%3Farnumber%3D4755480&authDecision=-203.
    Source
    System Sciences, 2009. HICSS '09. 42nd Hawaii International Conference
  7. Xiong, C.: Knowledge based text representations for information retrieval (2016) 0.40
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    Abstract
    The successes of information retrieval (IR) in recent decades were built upon bag-of-words representations. Effective as it is, bag-of-words is only a shallow text understanding; there is a limited amount of information for document ranking in the word space. This dissertation goes beyond words and builds knowledge based text representations, which embed the external and carefully curated information from knowledge bases, and provide richer and structured evidence for more advanced information retrieval systems. This thesis research first builds query representations with entities associated with the query. Entities' descriptions are used by query expansion techniques that enrich the query with explanation terms. Then we present a general framework that represents a query with entities that appear in the query, are retrieved by the query, or frequently show up in the top retrieved documents. A latent space model is developed to jointly learn the connections from query to entities and the ranking of documents, modeling the external evidence from knowledge bases and internal ranking features cooperatively. To further improve the quality of relevant entities, a defining factor of our query representations, we introduce learning to rank to entity search and retrieve better entities from knowledge bases. In the document representation part, this thesis research also moves one step forward with a bag-of-entities model, in which documents are represented by their automatic entity annotations, and the ranking is performed in the entity space.
    This proposal includes plans to improve the quality of relevant entities with a co-learning framework that learns from both entity labels and document labels. We also plan to develop a hybrid ranking system that combines word based and entity based representations together with their uncertainties considered. At last, we plan to enrich the text representations with connections between entities. We propose several ways to infer entity graph representations for texts, and to rank documents using their structure representations. This dissertation overcomes the limitation of word based representations with external and carefully curated information from knowledge bases. We believe this thesis research is a solid start towards the new generation of intelligent, semantic, and structured information retrieval.
    Content
    Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Language and Information Technologies. Vgl.: https%3A%2F%2Fwww.cs.cmu.edu%2F~cx%2Fpapers%2Fknowledge_based_text_representation.pdf&usg=AOvVaw0SaTSvhWLTh__Uz_HtOtl3.
  8. Popper, K.R.: Three worlds : the Tanner lecture on human values. Deliverd at the University of Michigan, April 7, 1978 (1978) 0.39
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    Source
    https%3A%2F%2Ftannerlectures.utah.edu%2F_documents%2Fa-to-z%2Fp%2Fpopper80.pdf&usg=AOvVaw3f4QRTEH-OEBmoYr2J_c7H
  9. Farazi, M.: Faceted lightweight ontologies : a formalization and some experiments (2010) 0.37
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    Abstract
    While classifications are heavily used to categorize web content, the evolution of the web foresees a more formal structure - ontology - which can serve this purpose. Ontologies are core artifacts of the Semantic Web which enable machines to use inference rules to conduct automated reasoning on data. Lightweight ontologies bridge the gap between classifications and ontologies. A lightweight ontology (LO) is an ontology representing a backbone taxonomy where the concept of the child node is more specific than the concept of the parent node. Formal lightweight ontologies can be generated from their informal ones. The key applications of formal lightweight ontologies are document classification, semantic search, and data integration. However, these applications suffer from the following problems: the disambiguation accuracy of the state of the art NLP tools used in generating formal lightweight ontologies from their informal ones; the lack of background knowledge needed for the formal lightweight ontologies; and the limitation of ontology reuse. In this dissertation, we propose a novel solution to these problems in formal lightweight ontologies; namely, faceted lightweight ontology (FLO). FLO is a lightweight ontology in which terms, present in each node label, and their concepts, are available in the background knowledge (BK), which is organized as a set of facets. A facet can be defined as a distinctive property of the groups of concepts that can help in differentiating one group from another. Background knowledge can be defined as a subset of a knowledge base, such as WordNet, and often represents a specific domain.
    Content
    PhD Dissertation at International Doctorate School in Information and Communication Technology. Vgl.: https%3A%2F%2Fcore.ac.uk%2Fdownload%2Fpdf%2F150083013.pdf&usg=AOvVaw2n-qisNagpyT0lli_6QbAQ.
    Imprint
    Trento : University / Department of information engineering and computer science
  10. Stojanovic, N.: Ontology-based Information Retrieval : methods and tools for cooperative query answering (2005) 0.36
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    Abstract
    By the explosion of possibilities for a ubiquitous content production, the information overload problem reaches the level of complexity which cannot be managed by traditional modelling approaches anymore. Due to their pure syntactical nature traditional information retrieval approaches did not succeed in treating content itself (i.e. its meaning, and not its representation). This leads to a very low usefulness of the results of a retrieval process for a user's task at hand. In the last ten years ontologies have been emerged from an interesting conceptualisation paradigm to a very promising (semantic) modelling technology, especially in the context of the Semantic Web. From the information retrieval point of view, ontologies enable a machine-understandable form of content description, such that the retrieval process can be driven by the meaning of the content. However, the very ambiguous nature of the retrieval process in which a user, due to the unfamiliarity with the underlying repository and/or query syntax, just approximates his information need in a query, implies a necessity to include the user in the retrieval process more actively in order to close the gap between the meaning of the content and the meaning of a user's query (i.e. his information need). This thesis lays foundation for such an ontology-based interactive retrieval process, in which the retrieval system interacts with a user in order to conceptually interpret the meaning of his query, whereas the underlying domain ontology drives the conceptualisation process. In that way the retrieval process evolves from a query evaluation process into a highly interactive cooperation between a user and the retrieval system, in which the system tries to anticipate the user's information need and to deliver the relevant content proactively. Moreover, the notion of content relevance for a user's query evolves from a content dependent artefact to the multidimensional context-dependent structure, strongly influenced by the user's preferences. This cooperation process is realized as the so-called Librarian Agent Query Refinement Process. In order to clarify the impact of an ontology on the retrieval process (regarding its complexity and quality), a set of methods and tools for different levels of content and query formalisation is developed, ranging from pure ontology-based inferencing to keyword-based querying in which semantics automatically emerges from the results. Our evaluation studies have shown that the possibilities to conceptualize a user's information need in the right manner and to interpret the retrieval results accordingly are key issues for realizing much more meaningful information retrieval systems.
    Content
    Vgl.: http%3A%2F%2Fdigbib.ubka.uni-karlsruhe.de%2Fvolltexte%2Fdocuments%2F1627&ei=tAtYUYrBNoHKtQb3l4GYBw&usg=AFQjCNHeaxKkKU3-u54LWxMNYGXaaDLCGw&sig2=8WykXWQoDKjDSdGtAakH2Q&bvm=bv.44442042,d.Yms.
    Theme
    Semantic Web
  11. Vetere, G.; Lenzerini, M.: Models for semantic interoperability in service-oriented architectures (2005) 0.34
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    Content
    Vgl.: http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=5386707&url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Farnumber%3D5386707.
  12. Malsburg, C. von der: ¬The correlation theory of brain function (1981) 0.30
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    Source
    http%3A%2F%2Fcogprints.org%2F1380%2F1%2FvdM_correlation.pdf&usg=AOvVaw0g7DvZbQPb2U7dYb49b9v_
    Theme
    Information
  13. Noever, D.; Ciolino, M.: ¬The Turing deception (2022) 0.30
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    Source
    https%3A%2F%2Farxiv.org%2Fabs%2F2212.06721&usg=AOvVaw3i_9pZm9y_dQWoHi6uv0EN
  14. Handbook on ontologies (2004) 0.16
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    LCSH
    Knowledge representation (Information theory)
    Conceptual structures (Information theory)
    RSWK
    Informationssystem / Wissenstechnik / Ontologie <Wissensverarbeitung> / Aufsatzsammlung
    Semantic Web / Wissensbasiertes System / Ontologie <Wissensverarbeitung> / Aufsatzsammlung
    Informationssystem / Konzeptionelle Modellierung / Ontologie <Wissensverarbeitung> / Aufsatzsammlung
    Series
    International handbook on information systems
    Subject
    Informationssystem / Wissenstechnik / Ontologie <Wissensverarbeitung> / Aufsatzsammlung
    Semantic Web / Wissensbasiertes System / Ontologie <Wissensverarbeitung> / Aufsatzsammlung
    Informationssystem / Konzeptionelle Modellierung / Ontologie <Wissensverarbeitung> / Aufsatzsammlung
    Knowledge representation (Information theory)
    Conceptual structures (Information theory)
    Theme
    Semantic Web
  15. Knowledge organization, information systems and other essays : professor A. Neelameghan Festschrift (2006) 0.11
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    Content
    Inhalt: KNOWLEDGE ORGANIZATION Towards a Future for Knowledge Organization Ingetraut Dahlberg Professor Neelameghan's Contribution to the Advancement and Development of Classification in the Context of Knowledge Organization Nancy J. Williamson Knowledge Orgnization System Over Time S. Seetharama The Facet Concept as a Universal Principle of Subdivisio Clare Beghtol Facet Analysis as a Knowledge Management Tool on the Internet Kathryn La Barre and Pauline Atherton Cochrane The Universal Decimal Classification: A Response to a Challenge I. C. Mellwaine Controlled Vocabularies as a Sphere of Influence Anita S. Coleman and Paul Bracke Aligning Systems of Relationship Rebecca Green and Carol A. Bean Terminologies, Ontologies and Information Access Widad Mustafa El Hadi SATSAN AUTOMATRIX Version 1 : A Computer Programme for Synthesis of Colon Class Number According to the Postulational Approach B. G. Satyapal and N. Sanjivini Satyapal. INTEROPERABILITY, DIGITAL LIBRARY AND INFORMATION RETRIEVAL Interoperable Institutional Digital Research Repositories and Their Potential for Open Access Research Knowledge Management T. B. Rajashekar Boundary Objects and the Digital Library Michael Shepherd and Corolyn Watters A PFT-based Approach to Make CDS/ISIS Data based OAI-Compliant Francis Jayakanth and L. Aswath The changing Language Technology and CDS/ ISIS: UNICODE and the Emergence of OTF K. H. Hussain and J. S. Rajeev Text Mining in Biomedicine: Challenges and Opportunities Padmini Srinivasan Determining Authorship of Web Pages Timothy C. Craven
    KNOWLEDGE MANAGEMENT IN SPECIALIZED AREAS Information System for Knowledge Management in the Specialized Division of a Hospital M. C. Vasudevan; Murali Mohan and Amit Kapoor Five Laws of Information Service and Architecting Knowledge Infrastructure for Education and Development k. R. Srivathsan Documentation of Compositions in Carnatic Music: Need for and Utility of a Computerized Database K. S. Nagarajan Saint Tyagaraja CD: A Model for Knowledge Organization and Presentation of Classical Carnatic Music---T. N. Rajan The National Tuberculosis Institute, Bangalore; Recent Development in Library and Information Services Sudha S. Murthy Sri Ramakrishna Math Libraries: Computer Applications D.N. Nagaraja Rao Save the Time of the Godly: Information Mediator's Role in Promoting Spiritual and Religious Accommodation Mohamed Taher INFORMATION SOCIETY Information Society, Information Networks and National Development : An Overview P. B. Mangla Digital Divide in India-Narrowing the Gap: An Appraisal with Special Reference to Karnataka K. N. Prasad Future of the Book: Will the Printed Book Survive the Digital Age? K. A. Isaac Role of Traditional Librarianship in the Internet/Digital Era a. Ratnakar A New Paradigm of Education System for Reaching the Unreached Through Open and Distance Education with Special Reference to the Indian Initiative S. B. Ghosh Knowledge Workers of the New Millennium: An Instance of Interdisciplinary Exchange and Discovery Michael Medland
    RSWK
    Wissensorganisation / Aufsatzsammlung (GBV)
    Indien / Wissensbasiertes System / Aufsatzsammlung (SWB)
    Indien / Informations- und Dokumentationswissenschaft / Aufsatzsammlung (SWB)
    Dewey-Dezimalklassifikation / Elektronische Bibliothek / Informationsgesellschaft / Information Retrieval (GBV)
    Subject
    Wissensorganisation / Aufsatzsammlung (GBV)
    Indien / Wissensbasiertes System / Aufsatzsammlung (SWB)
    Indien / Informations- und Dokumentationswissenschaft / Aufsatzsammlung (SWB)
    Dewey-Dezimalklassifikation / Elektronische Bibliothek / Informationsgesellschaft / Information Retrieval (GBV)
  16. Jung, H.; Yi, E.; Kim, D.; Lee, G.G.: Information extraction with automatic knowledge expansion (2005) 0.10
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    Abstract
    POSIE (POSTECH Information Extraction System) is an information extraction system which uses multiple learning strategies, i.e., SmL, user-oriented learning, and separate-context learning, in a question answering framework. POSIE replaces laborious annotation with automatic instance extraction by the SmL from structured Web documents, and places the user at the end of the user-oriented learning cycle. Information extraction as question answering simplifies the extraction procedures for a set of slots. We introduce the techniques verified on the question answering framework, such as domain knowledge and instance rules, into an information extraction problem. To incrementally improve extraction performance, a sequence of the user-oriented learning and the separate-context learning produces context rules and generalizes them in both the learning and extraction phases. Experiments on the "continuing education" domain initially show that the F1-measure becomes 0.477 and recall 0.748 with no user training. However, as the size of the training documents grows, the F1-measure reaches beyond 0.75 with recall 0.772. We also obtain F-measure of about 0.9 for five out of seven slots on "job offering" domain.
    Source
    Information processing and management. 41(2005) no.2, S.217-242
  17. Semantic applications (2018) 0.10
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    Content
    Introduction.- Ontology Development.- Compliance using Metadata.- Variety Management for Big Data.- Text Mining in Economics.- Generation of Natural Language Texts.- Sentiment Analysis.- Building Concise Text Corpora from Web Contents.- Ontology-Based Modelling of Web Content.- Personalized Clinical Decision Support for Cancer Care.- Applications of Temporal Conceptual Semantic Systems.- Context-Aware Documentation in the Smart Factory.- Knowledge-Based Production Planning for Industry 4.0.- Information Exchange in Jurisdiction.- Supporting Automated License Clearing.- Managing cultural assets: Implementing typical cultural heritage archive's usage scenarios via Semantic Web technologies.- Semantic Applications for Process Management.- Domain-Specific Semantic Search Applications.
    LCSH
    Information storage and retrieval
    Management information systems
    Information Systems Applications (incl. Internet)
    Management of Computing and Information Systems
    Information Storage and Retrieval
    RSWK
    Wissensbasiertes System
    Information Retrieval
    Semantic Web
    Subject
    Wissensbasiertes System
    Information Retrieval
    Semantic Web
    Information storage and retrieval
    Management information systems
    Information Systems Applications (incl. Internet)
    Management of Computing and Information Systems
    Information Storage and Retrieval
    Theme
    Semantic Web
  18. Goh, A.; Hui, S.C.: TES: a text extraction system (1996) 0.09
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    Abstract
    With the onset of the information explosion arising from digital libraries and access to a wealth of information through the Internet, the need to efficiently determine the relevance of a document becomes even more urgent. Describes a text extraction system (TES), which retrieves a set of sentences from a document to form an indicative abstract. Such an automated process enables information to be filtered more quickly. Discusses the combination of various text extraction techniques. Compares results with manually produced abstracts
    Date
    26. 2.1997 10:22:43
    Source
    Microcomputers for information management. 13(1996) no.1, S.41-55
  19. Multi-source, multilingual information extraction and summarization (2013) 0.08
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    Abstract
    Information extraction (IE) and text summarization (TS) are powerful technologies for finding relevant pieces of information in text and presenting them to the user in condensed form. The ongoing information explosion makes IE and TS critical for successful functioning within the information society. These technologies face particular challenges due to the inherent multi-source nature of the information explosion. The technologies must now handle not isolated texts or individual narratives, but rather large-scale repositories and streams---in general, in multiple languages---containing a multiplicity of perspectives, opinions, or commentaries on particular topics, entities or events. There is thus a need to adapt existing techniques and develop new ones to deal with these challenges. This volume contains a selection of papers that present a variety of methodologies for content identification and extraction, as well as for content fusion and regeneration. The chapters cover various aspects of the challenges, depending on the nature of the information sought---names vs. events,--- and the nature of the sources---news streams vs. image captions vs. scientific research papers, etc. This volume aims to offer a broad and representative sample of studies from this very active research field.
    RSWK
    Natürlichsprachiges System / Information Extraction / Automatische Inhaltsanalyse / Zusammenfassung / Aufsatzsammlung
    Subject
    Natürlichsprachiges System / Information Extraction / Automatische Inhaltsanalyse / Zusammenfassung / Aufsatzsammlung
  20. Riloff, E.: ¬An empirical study of automated dictionary construction for information extraction in three domains (1996) 0.08
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    Abstract
    AutoSlog is a system that addresses the knowledge engineering bottleneck for information extraction. AutoSlog automatically creates domain specific dictionaries for information extraction, given an appropriate training corpus. Describes experiments with AutoSlog in terrorism, joint ventures and microelectronics domains. Compares the performance of AutoSlog across the 3 domains, discusses the lessons learned and presents results from 2 experiments which demonstrate that novice users can generate effective dictionaries using AutoSlog
    Date
    6. 3.1997 16:22:15

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