Search (2 results, page 1 of 1)

0.01596949 = product of:
  0.06387796 = sum of:
    0.06387796 = weight(_text_:term in 4041) [ClassicSimilarity], result of:
      0.06387796 = score(doc=4041,freq=4.0), product of:
        0.21904005 = queryWeight, product of:
          4.66603 = idf(docFreq=1130, maxDocs=44218)
          0.04694356 = queryNorm
        0.29162687 = fieldWeight in 4041, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          4.66603 = idf(docFreq=1130, maxDocs=44218)
          0.03125 = fieldNorm(doc=4041)
  0.25 = coord(1/4)

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.

0.002548521 = product of:
  0.010194084 = sum of:
    0.010194084 = product of:
      0.040776335 = sum of:
        0.040776335 = weight(_text_:based in 5204) [ClassicSimilarity], result of:
          0.040776335 = score(doc=5204,freq=6.0), product of:
            0.14144066 = queryWeight, product of:
              3.0129938 = idf(docFreq=5906, maxDocs=44218)
              0.04694356 = queryNorm
            0.28829288 = fieldWeight in 5204, product of:
              2.4494898 = tf(freq=6.0), with freq of:
                6.0 = termFreq=6.0
              3.0129938 = idf(docFreq=5906, maxDocs=44218)
              0.0390625 = fieldNorm(doc=5204)
      0.25 = coord(1/4)
  0.25 = coord(1/4)

Abstract

This book describes proven methodologies for developing semantic applications: software applications which explicitly or implicitly uses the semantics (i.e., the meaning) of a domain terminology in order to improve usability, correctness, and completeness. An example is semantic search, where synonyms and related terms are used for enriching the results of a simple text-based search. Ontologies, thesauri or controlled vocabularies are the centerpiece of semantic applications. The book includes technological and architectural best practices for corporate use.

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.