Search (7 results, page 1 of 1)

0.029319597 = product of:
  0.07329899 = sum of:
    0.040348392 = weight(_text_:context in 5204) [ClassicSimilarity], result of:
      0.040348392 = score(doc=5204,freq=2.0), product of:
        0.17622331 = queryWeight, product of:
          4.14465 = idf(docFreq=1904, maxDocs=44218)
          0.04251826 = queryNorm
        0.22896172 = fieldWeight in 5204, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          4.14465 = idf(docFreq=1904, maxDocs=44218)
          0.0390625 = fieldNorm(doc=5204)
    0.032950602 = weight(_text_:system in 5204) [ClassicSimilarity], result of:
      0.032950602 = score(doc=5204,freq=4.0), product of:
        0.13391352 = queryWeight, product of:
          3.1495528 = idf(docFreq=5152, maxDocs=44218)
          0.04251826 = queryNorm
        0.24605882 = fieldWeight in 5204, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          3.1495528 = idf(docFreq=5152, maxDocs=44218)
          0.0390625 = fieldNorm(doc=5204)
  0.4 = coord(2/5)

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.

RSWK

Wissensbasiertes System

Subject

Wissensbasiertes System

0.027752852 = product of:
  0.06938213 = sum of:
    0.050742455 = weight(_text_:index in 4041) [ClassicSimilarity], result of:
      0.050742455 = score(doc=4041,freq=4.0), product of:
        0.18579477 = queryWeight, product of:
          4.369764 = idf(docFreq=1520, maxDocs=44218)
          0.04251826 = queryNorm
        0.27311024 = fieldWeight in 4041, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          4.369764 = idf(docFreq=1520, maxDocs=44218)
          0.03125 = fieldNorm(doc=4041)
    0.018639674 = weight(_text_:system in 4041) [ClassicSimilarity], result of:
      0.018639674 = score(doc=4041,freq=2.0), product of:
        0.13391352 = queryWeight, product of:
          3.1495528 = idf(docFreq=5152, maxDocs=44218)
          0.04251826 = queryNorm
        0.13919188 = fieldWeight in 4041, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.1495528 = idf(docFreq=5152, maxDocs=44218)
          0.03125 = fieldNorm(doc=4041)
  0.4 = coord(2/5)

Content

Inhalt: Boolean retrieval - The term vocabulary & postings lists - Dictionaries and tolerant retrieval - Index construction - Index compression - Scoring, term weighting & the vector space model - Computing scores in a complete search system - Evaluation in information retrieval - Relevance feedback & query expansion - XML retrieval - Probabilistic information retrieval - Language models for information retrieval - Text classification & Naive Bayes - Vector space classification - Support vector machines & machine learning on documents - Flat clustering - Hierarchical clustering - Matrix decompositions & latent semantic indexing - Web search basics - Web crawling and indexes - Link analysis Vgl. die digitale Fassung unter: http://nlp.stanford.edu/IR-book/pdf/irbookprint.pdf.

0.008069678 = product of:
  0.040348392 = sum of:
    0.040348392 = weight(_text_:context in 2396) [ClassicSimilarity], result of:
      0.040348392 = score(doc=2396,freq=2.0), product of:
        0.17622331 = queryWeight, product of:
          4.14465 = idf(docFreq=1904, maxDocs=44218)
          0.04251826 = queryNorm
        0.22896172 = fieldWeight in 2396, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          4.14465 = idf(docFreq=1904, maxDocs=44218)
          0.0390625 = fieldNorm(doc=2396)
  0.2 = coord(1/5)

Abstract

Natural Language is not only the most important means of communication between human beings, it is also used over historical periods for the preservation of cultural achievements and their transmission from one generation to the other. During the last few decades, the flod of digitalized information has been growing tremendously. This tendency will continue with the globalisation of information societies and with the growing importance of national and international computer networks. This is one reason why the theoretical understanding and the automated treatment of communication processes based on natural language have such a decisive social and economic impact. In this context, the semantic representation of knowledge originally formulated in natural language plays a central part, because it connects all components of natural language processing systems, be they the automatic understanding of natural language (analysis), the rational reasoning over knowledge bases, or the generation of natural language expressions from formal representations. This book presents a method for the semantic representation of natural language expressions (texts, sentences, phrases, etc.) which can be used as a universal knowledge representation paradigm in the human sciences, like linguistics, cognitive psychology, or philosophy of language, as well as in computational linguistics and in artificial intelligence. It is also an attempt to close the gap between these disciplines, which to a large extent are still working separately.

0.0071760663 = product of:
  0.03588033 = sum of:
    0.03588033 = weight(_text_:index in 362) [ClassicSimilarity], result of:
      0.03588033 = score(doc=362,freq=2.0), product of:
        0.18579477 = queryWeight, product of:
          4.369764 = idf(docFreq=1520, maxDocs=44218)
          0.04251826 = queryNorm
        0.1931181 = fieldWeight in 362, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          4.369764 = idf(docFreq=1520, maxDocs=44218)
          0.03125 = fieldNorm(doc=362)
  0.2 = coord(1/5)

Content

Inhalt: An Introduction to Text Mining.- Information Extraction from Text.- A Survey of Text Summarization Techniques.- A Survey of Text Clustering Algorithms.- Dimensionality Reduction and Topic Modeling.- A Survey of Text Classification Algorithms.- Transfer Learning for Text Mining.- Probabilistic Models for Text Mining.- Mining Text Streams.- Translingual Mining from Text Data.- Text Mining in Multimedia.- Text Analytics in Social Media.- A Survey of Opinion Mining and Sentiment Analysis.- Biomedical Text Mining: A Survey of Recent Progress.- Index.

0.0065901205 = product of:
  0.032950602 = sum of:
    0.032950602 = weight(_text_:system in 978) [ClassicSimilarity], result of:
      0.032950602 = score(doc=978,freq=4.0), product of:
        0.13391352 = queryWeight, product of:
          3.1495528 = idf(docFreq=5152, maxDocs=44218)
          0.04251826 = queryNorm
        0.24605882 = fieldWeight in 978, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          3.1495528 = idf(docFreq=5152, maxDocs=44218)
          0.0390625 = fieldNorm(doc=978)
  0.2 = coord(1/5)

RSWK

Natürlichsprachiges System / Information Extraction / Automatische Inhaltsanalyse / Zusammenfassung / Aufsatzsammlung

Subject

Natürlichsprachiges System / Information Extraction / Automatische Inhaltsanalyse / Zusammenfassung / Aufsatzsammlung

0.0046599186 = product of:
  0.023299592 = sum of:
    0.023299592 = weight(_text_:system in 2731) [ClassicSimilarity], result of:
      0.023299592 = score(doc=2731,freq=2.0), product of:
        0.13391352 = queryWeight, product of:
          3.1495528 = idf(docFreq=5152, maxDocs=44218)
          0.04251826 = queryNorm
        0.17398985 = fieldWeight in 2731, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.1495528 = idf(docFreq=5152, maxDocs=44218)
          0.0390625 = fieldNorm(doc=2731)
  0.2 = coord(1/5)

Abstract

Das Buch gibt eine umfassende Darstellung einer Methodik zur Interpretation und Bedeutungsrepräsentation natürlichsprachlicher Ausdrücke. Diese Methodik der "Mehrschichtigen Erweiterten Semantischen Netze", das sogenannte MultiNet-Paradigma, ist sowohl für theoretische Untersuchungen als auch für die automatische Verarbeitung natürlicher Sprache auf dem Rechner geeignet. Im ersten Teil des zweiteiligen Buches werden grundlegende Probleme der semantischen Repräsentation von Wissen bzw. der semantischen Interpretation natürlichsprachlicher Phänomene behandelt. Der zweite Teil enthält eine systematische Zusammenstellung des gesamten Repertoires von Darstellungsmitteln, die jeweils nach einem einheitlichen Schema beschrieben werden. Er dient als Kompendium der im Buch verwendeten formalen Beschreibungsmittel von MultiNet. Die vorgestellten Ergebnisse sind eingebettet in ein System von Software-Werkzeugen, die eine praktische Nutzung der MultiNet-Darstellungsmittel als Formalismus zur Bedeutungsrepräsentation im Rahmen der automatischen Sprachverarbeitung sichern. Hierzu gehören: eine Werkbank für den Wissensingenieur, ein Übersetzungssystem zur automatischen Gewinnung von Bedeutungsdarstellungen natürlichsprachlicher Sätze und eine Werkbank für den Computerlexikographen. Der Inhalt des Buches beruht auf jahrzehntelanger Forschung auf dem Gebiet der automatischen Sprachverarbeitung und wurde mit Vorlesungen zur Künstlichen Intelligenz und Wissensverarbeitung an der TU Dresden und der FernUniversität Hagen wiederholt in der Hochschullehre eingesetzt. Als Vorkenntnisse werden beim Leser lediglich Grundlagen der traditionellen Grammatik und elementare Kenntnisse der Prädikatenlogik vorausgesetzt.

0.0046130843 = product of:
  0.02306542 = sum of:
    0.02306542 = weight(_text_:system in 167) [ClassicSimilarity], result of:
      0.02306542 = score(doc=167,freq=4.0), product of:
        0.13391352 = queryWeight, product of:
          3.1495528 = idf(docFreq=5152, maxDocs=44218)
          0.04251826 = queryNorm
        0.17224117 = fieldWeight in 167, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          3.1495528 = idf(docFreq=5152, maxDocs=44218)
          0.02734375 = fieldNorm(doc=167)
  0.2 = coord(1/5)

RSWK

Semantic Web / Information Extraction / Suche / Wissensbasiertes System / Aufsatzsammlung

Subject

Semantic Web / Information Extraction / Suche / Wissensbasiertes System / Aufsatzsammlung