Search (23 results, page 1 of 2)

  • × year_i:[1990 TO 2000}
  • × theme_ss:"Semantisches Umfeld in Indexierung u. Retrieval"
  1. Fieldhouse, M.; Hancock-Beaulieu, M.: ¬The design of a graphical user interface for a highly interactive information retrieval system (1996) 0.05
    0.051698353 = product of:
      0.10339671 = sum of:
        0.10339671 = sum of:
          0.053905163 = weight(_text_:systems in 6958) [ClassicSimilarity], result of:
            0.053905163 = score(doc=6958,freq=4.0), product of:
              0.16037072 = queryWeight, product of:
                3.0731742 = idf(docFreq=5561, maxDocs=44218)
                0.052184064 = queryNorm
              0.33612844 = fieldWeight in 6958, product of:
                2.0 = tf(freq=4.0), with freq of:
                  4.0 = termFreq=4.0
                3.0731742 = idf(docFreq=5561, maxDocs=44218)
                0.0546875 = fieldNorm(doc=6958)
          0.049491543 = weight(_text_:22 in 6958) [ClassicSimilarity], result of:
            0.049491543 = score(doc=6958,freq=2.0), product of:
              0.1827397 = queryWeight, product of:
                3.5018296 = idf(docFreq=3622, maxDocs=44218)
                0.052184064 = queryNorm
              0.2708308 = fieldWeight in 6958, product of:
                1.4142135 = tf(freq=2.0), with freq of:
                  2.0 = termFreq=2.0
                3.5018296 = idf(docFreq=3622, maxDocs=44218)
                0.0546875 = fieldNorm(doc=6958)
      0.5 = coord(1/2)
    
    Abstract
    Reports on the design of a GUI for the Okapi 'best match' retrieval system developed at the Centre for Interactive Systems Research, City University, UK, for online library catalogues. The X-Windows interface includes an interactive query expansion (IQE) facilty which involves the user in the selection of query terms to reformulate a search. Presents the design rationale, based on a game board metaphor, and describes the features of each of the stages of the search interaction. Reports on the early operational field trial and discusses relevant evaluation issues and objectives
    Source
    Information retrieval: new systems and current research. Proceedings of the 16th Research Colloquium of the British Computer Society Information Retrieval Specialist Group, Drymen, Scotland, 22-23 Mar 94. Ed.: R. Leon
  2. Chang, C.-H.; Hsu, C.-C.: Integrating query expansion and conceptual relevance feedback for personalized Web information retrieval (1998) 0.04
    0.043804124 = product of:
      0.08760825 = sum of:
        0.08760825 = sum of:
          0.038116705 = weight(_text_:systems in 1319) [ClassicSimilarity], result of:
            0.038116705 = score(doc=1319,freq=2.0), product of:
              0.16037072 = queryWeight, product of:
                3.0731742 = idf(docFreq=5561, maxDocs=44218)
                0.052184064 = queryNorm
              0.23767869 = fieldWeight in 1319, product of:
                1.4142135 = tf(freq=2.0), with freq of:
                  2.0 = termFreq=2.0
                3.0731742 = idf(docFreq=5561, maxDocs=44218)
                0.0546875 = fieldNorm(doc=1319)
          0.049491543 = weight(_text_:22 in 1319) [ClassicSimilarity], result of:
            0.049491543 = score(doc=1319,freq=2.0), product of:
              0.1827397 = queryWeight, product of:
                3.5018296 = idf(docFreq=3622, maxDocs=44218)
                0.052184064 = queryNorm
              0.2708308 = fieldWeight in 1319, product of:
                1.4142135 = tf(freq=2.0), with freq of:
                  2.0 = termFreq=2.0
                3.5018296 = idf(docFreq=3622, maxDocs=44218)
                0.0546875 = fieldNorm(doc=1319)
      0.5 = coord(1/2)
    
    Date
    1. 8.1996 22:08:06
    Source
    Computer networks and ISDN systems. 30(1998) nos.1/7, S.621-623
  3. Järvelin, K.; Kristensen, J.; Niemi, T.; Sormunen, E.; Keskustalo, H.: ¬A deductive data model for query expansion (1996) 0.04
    0.03754639 = product of:
      0.07509278 = sum of:
        0.07509278 = sum of:
          0.03267146 = weight(_text_:systems in 2230) [ClassicSimilarity], result of:
            0.03267146 = score(doc=2230,freq=2.0), product of:
              0.16037072 = queryWeight, product of:
                3.0731742 = idf(docFreq=5561, maxDocs=44218)
                0.052184064 = queryNorm
              0.2037246 = fieldWeight in 2230, product of:
                1.4142135 = tf(freq=2.0), with freq of:
                  2.0 = termFreq=2.0
                3.0731742 = idf(docFreq=5561, maxDocs=44218)
                0.046875 = fieldNorm(doc=2230)
          0.042421322 = weight(_text_:22 in 2230) [ClassicSimilarity], result of:
            0.042421322 = score(doc=2230,freq=2.0), product of:
              0.1827397 = queryWeight, product of:
                3.5018296 = idf(docFreq=3622, maxDocs=44218)
                0.052184064 = queryNorm
              0.23214069 = fieldWeight in 2230, product of:
                1.4142135 = tf(freq=2.0), with freq of:
                  2.0 = termFreq=2.0
                3.5018296 = idf(docFreq=3622, maxDocs=44218)
                0.046875 = fieldNorm(doc=2230)
      0.5 = coord(1/2)
    
    Abstract
    We present a deductive data model for concept-based query expansion. It is based on three abstraction levels: the conceptual, linguistic and occurrence levels. Concepts and relationships among them are represented at the conceptual level. The expression level represents natural language expressions for concepts. Each expression has one or more matching models at the occurrence level. Each model specifies the matching of the expression in database indices built in varying ways. The data model supports a concept-based query expansion and formulation tool, the ExpansionTool, for environments providing heterogeneous IR systems. Expansion is controlled by adjustable matching reliability.
    Source
    Proceedings of the 19th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (ACM SIGIR '96), Zürich, Switzerland, August 18-22, 1996. Eds.: H.P. Frei et al
  4. Efthimiadis, E.N.: Approaches to search formulation and query expansion in information systems : DRS, DBMS, ES (1992) 0.03
    0.030439837 = product of:
      0.060879674 = sum of:
        0.060879674 = product of:
          0.12175935 = sum of:
            0.12175935 = weight(_text_:systems in 3871) [ClassicSimilarity], result of:
              0.12175935 = score(doc=3871,freq=10.0), product of:
                0.16037072 = queryWeight, product of:
                  3.0731742 = idf(docFreq=5561, maxDocs=44218)
                  0.052184064 = queryNorm
                0.75923675 = fieldWeight in 3871, product of:
                  3.1622777 = tf(freq=10.0), with freq of:
                    10.0 = termFreq=10.0
                  3.0731742 = idf(docFreq=5561, maxDocs=44218)
                  0.078125 = fieldNorm(doc=3871)
          0.5 = coord(1/2)
      0.5 = coord(1/2)
    
    Abstract
    Discusses the ways in which systems and/or users formulate and reformulate searches in documents retrieval systems (DRS), database management systems (DBMS) and expert systems (ES). Concludes that query formulation and reformulation has been neglected in these fields
  5. Ekmekcioglu, F.C.; Robertson, A.M.; Willett, P.: Effectiveness of query expansion in ranked-output document retrieval systems (1992) 0.02
    0.015401474 = product of:
      0.030802948 = sum of:
        0.030802948 = product of:
          0.061605897 = sum of:
            0.061605897 = weight(_text_:systems in 5689) [ClassicSimilarity], result of:
              0.061605897 = score(doc=5689,freq=4.0), product of:
                0.16037072 = queryWeight, product of:
                  3.0731742 = idf(docFreq=5561, maxDocs=44218)
                  0.052184064 = queryNorm
                0.38414678 = fieldWeight in 5689, product of:
                  2.0 = tf(freq=4.0), with freq of:
                    4.0 = termFreq=4.0
                  3.0731742 = idf(docFreq=5561, maxDocs=44218)
                  0.0625 = fieldNorm(doc=5689)
          0.5 = coord(1/2)
      0.5 = coord(1/2)
    
    Abstract
    Reports an evaluation of 3 methods for the expansion of natural language queries in ranked output retrieval systems. The methods are based on term co-occurrence data, on Soundex codes, and on a string similarity measure. Searches for 110 queries in a data base of 26.280 titles and abstracts suggest that there is no significant difference in retrieval effectiveness between any of these methods and unexpanded searches
  6. Robertson, A.M.; Willett, P.: Applications of n-grams in textual information systems (1998) 0.02
    0.015401474 = product of:
      0.030802948 = sum of:
        0.030802948 = product of:
          0.061605897 = sum of:
            0.061605897 = weight(_text_:systems in 4715) [ClassicSimilarity], result of:
              0.061605897 = score(doc=4715,freq=4.0), product of:
                0.16037072 = queryWeight, product of:
                  3.0731742 = idf(docFreq=5561, maxDocs=44218)
                  0.052184064 = queryNorm
                0.38414678 = fieldWeight in 4715, product of:
                  2.0 = tf(freq=4.0), with freq of:
                    4.0 = termFreq=4.0
                  3.0731742 = idf(docFreq=5561, maxDocs=44218)
                  0.0625 = fieldNorm(doc=4715)
          0.5 = coord(1/2)
      0.5 = coord(1/2)
    
    Abstract
    Provides an introduction to the use of n-grams in textual information systems, where an n-gram is a string of n, usually adjacent, characters, extracted from a section of continuous text. Applications that can be implemented efficiently and effectively using sets of n-grams include spelling errors detection and correction, query expansion, information retrieval with serial, inverted and signature files, dictionary look up, text compression, and language identification
  7. Efthimiadis, E.N.: End-users' understanding of thesaural knowledge structures in interactive query expansion (1994) 0.01
    0.014140441 = product of:
      0.028280882 = sum of:
        0.028280882 = product of:
          0.056561764 = sum of:
            0.056561764 = weight(_text_:22 in 5693) [ClassicSimilarity], result of:
              0.056561764 = score(doc=5693,freq=2.0), product of:
                0.1827397 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.052184064 = queryNorm
                0.30952093 = fieldWeight in 5693, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.0625 = fieldNorm(doc=5693)
          0.5 = coord(1/2)
      0.5 = coord(1/2)
    
    Date
    30. 3.2001 13:35:22
  8. Principles of semantic networks : explorations in the representation of knowledge (1991) 0.01
    0.013613109 = product of:
      0.027226217 = sum of:
        0.027226217 = product of:
          0.054452434 = sum of:
            0.054452434 = weight(_text_:systems in 1677) [ClassicSimilarity], result of:
              0.054452434 = score(doc=1677,freq=2.0), product of:
                0.16037072 = queryWeight, product of:
                  3.0731742 = idf(docFreq=5561, maxDocs=44218)
                  0.052184064 = queryNorm
                0.339541 = fieldWeight in 1677, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.0731742 = idf(docFreq=5561, maxDocs=44218)
                  0.078125 = fieldNorm(doc=1677)
          0.5 = coord(1/2)
      0.5 = coord(1/2)
    
    Abstract
    Enthält 3 thematische Sektionen: (1) Issues in knowledge representation; (2) formal analyses; (3) systems for knowledge representation
  9. Lund, K.; Burgess, C.; Atchley, R.A.: Semantic and associative priming in high-dimensional semantic space (1995) 0.01
    0.012372886 = product of:
      0.024745772 = sum of:
        0.024745772 = product of:
          0.049491543 = sum of:
            0.049491543 = weight(_text_:22 in 2151) [ClassicSimilarity], result of:
              0.049491543 = score(doc=2151,freq=2.0), product of:
                0.1827397 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.052184064 = queryNorm
                0.2708308 = fieldWeight in 2151, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.0546875 = fieldNorm(doc=2151)
          0.5 = coord(1/2)
      0.5 = coord(1/2)
    
    Source
    Proceedings of the Seventeenth Annual Conference of the Cognitive Science Society: July 22 - 25, 1995, University of Pittsburgh / ed. by Johanna D. Moore and Jill Fain Lehmann
  10. Rudolph, S.; Hemmje, M.: Visualisierung von Thesauri zur interaktiven Unterstüzung von visuellen Anfragen an Textdatenbanken (1994) 0.01
    0.011789299 = product of:
      0.023578597 = sum of:
        0.023578597 = product of:
          0.047157194 = sum of:
            0.047157194 = weight(_text_:systems in 2382) [ClassicSimilarity], result of:
              0.047157194 = score(doc=2382,freq=6.0), product of:
                0.16037072 = queryWeight, product of:
                  3.0731742 = idf(docFreq=5561, maxDocs=44218)
                  0.052184064 = queryNorm
                0.29405114 = fieldWeight in 2382, product of:
                  2.4494898 = tf(freq=6.0), with freq of:
                    6.0 = termFreq=6.0
                  3.0731742 = idf(docFreq=5561, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=2382)
          0.5 = coord(1/2)
      0.5 = coord(1/2)
    
    Abstract
    In der folgenden Studie wird eine Komponente für eine visuelle Benutzerschnittstelle zu Textdatenbanken entworfen. Mit Hilfe einer Terminologievisualisierung wird dem Benutzer eine Hilfestellung bei der Relevanzbewertung von Dokumenten und bei der Erweiterung seiner visuellen Anfrage an das Retrieval-System gegeben. Dazu werden zuerst die grundlegenden Information-Retrieval-Modelle eingehender vorgestellt, d.h., generelle Retrieval-Modelle, Retrievaloperationen und spezielle Retrieval-Modelle wie Text-Retrieval werden erläutert. Die Funktionalität eines Text-Retrieval-Systems wird vorgestellt. Darüber hinaus werden bereits existierende Implementierungen visueller Information-Retrieval-Benutzerschnittstellen vorgestellt. Im weiteren Verlauf der Arbeit werden mögliche Visualisierungen der mit Hilfe eines Text-Retrieval-Systems gefundenen Dokumente aufgezeigt. Es werden mehrere Vorschläge zur Visualisierung von Thesauri diskutiert. Es wird gezeigt, wie neuronale Netze zur Kartierung eines Eingabebereiches benutzt werden können. Klassifikationsebenen einer objekt-orientierten Annäherung eines Information-Retrieval-Systems werden vorgestellt. In diesem Zusammenhang werden auch die Eigenschaften von Thesauri sowie die Architektur und Funktion eines Parsersystems erläutert. Mit diesen Voraussetzung wird die Implementierung einer visuellen Terminologierunterstützung realisiert. Abschließend wird ein Fazit zur vorgestellten Realisierung basierend auf einem Drei-Schichten-Modell von [Agosti et al. 1990] gezogen.
  11. Nagao, M.: Knowledge and inference (1990) 0.01
    0.011789299 = product of:
      0.023578597 = sum of:
        0.023578597 = product of:
          0.047157194 = sum of:
            0.047157194 = weight(_text_:systems in 3304) [ClassicSimilarity], result of:
              0.047157194 = score(doc=3304,freq=6.0), product of:
                0.16037072 = queryWeight, product of:
                  3.0731742 = idf(docFreq=5561, maxDocs=44218)
                  0.052184064 = queryNorm
                0.29405114 = fieldWeight in 3304, product of:
                  2.4494898 = tf(freq=6.0), with freq of:
                    6.0 = termFreq=6.0
                  3.0731742 = idf(docFreq=5561, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=3304)
          0.5 = coord(1/2)
      0.5 = coord(1/2)
    
    Abstract
    Knowledge and Inference discusses an important problem for software systems: How do we treat knowledge and ideas on a computer and how do we use inference to solve problems on a computer? The book talks about the problems of knowledge and inference for the purpose of merging artificial intelligence and library science. The book begins by clarifying the concept of ""knowledge"" from many points of view, followed by a chapter on the current state of library science and the place of artificial intelligence in library science. Subsequent chapters cover central topics in the artificial intelligence: search and problem solving, methods of making proofs, and the use of knowledge in looking for a proof. There is also a discussion of how to use the knowledge system. The final chapter describes a popular expert system. It describes tools for building expert systems using an example based on Expert Systems-A Practical Introduction by P. Sell (Macmillian, 1985). This type of software is called an ""expert system shell."" This book was written as a textbook for undergraduate students covering only the basics but explaining as much detail as possible.
  12. Poynder, R.: Web research engines? (1996) 0.01
    0.011551105 = product of:
      0.02310221 = sum of:
        0.02310221 = product of:
          0.04620442 = sum of:
            0.04620442 = weight(_text_:systems in 5698) [ClassicSimilarity], result of:
              0.04620442 = score(doc=5698,freq=4.0), product of:
                0.16037072 = queryWeight, product of:
                  3.0731742 = idf(docFreq=5561, maxDocs=44218)
                  0.052184064 = queryNorm
                0.28811008 = fieldWeight in 5698, product of:
                  2.0 = tf(freq=4.0), with freq of:
                    4.0 = termFreq=4.0
                  3.0731742 = idf(docFreq=5561, maxDocs=44218)
                  0.046875 = fieldNorm(doc=5698)
          0.5 = coord(1/2)
      0.5 = coord(1/2)
    
    Abstract
    Describes the shortcomings of search engines for the WWW comparing their current capabilities to those of the first generation CD-ROM products. Some allow phrase searching and most are improving their Boolean searching. Few allow truncation, wild cards or nested logic. They are stateless, losing previous search criteria. Unlike the indexing and classification systems for today's CD-ROMs, those for Web pages are random, unstructured and of variable quality. Considers that at best Web search engines can only offer free text searching. Discusses whether automatic data classification systems such as Infoseek Ultra can overcome the haphazard nature of the Web with neural network technology, and whether Boolean search techniques may be redundant when replaced by technology such as the Euroferret search engine. However, artificial intelligence is rarely successful on huge, varied databases. Relevance ranking and automatic query expansion still use the same simple inverted indexes. Most Web search engines do nothing more than word counting. Further complications arise with foreign languages
  13. Gödert, W.: Inhaltliche Dokumenterschließung, Information Retrieval und Navigation in Informationsräumen (1995) 0.01
    0.010890487 = product of:
      0.021780973 = sum of:
        0.021780973 = product of:
          0.043561947 = sum of:
            0.043561947 = weight(_text_:systems in 4438) [ClassicSimilarity], result of:
              0.043561947 = score(doc=4438,freq=2.0), product of:
                0.16037072 = queryWeight, product of:
                  3.0731742 = idf(docFreq=5561, maxDocs=44218)
                  0.052184064 = queryNorm
                0.2716328 = fieldWeight in 4438, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.0731742 = idf(docFreq=5561, maxDocs=44218)
                  0.0625 = fieldNorm(doc=4438)
          0.5 = coord(1/2)
      0.5 = coord(1/2)
    
    Abstract
    Examines the advantages and disadvantages of precoordinated, postcoordinated and automatic indexing with regard to existing information storage systems, such as card catalogues, OPACs, CR-ROM databases, and online databases. Presents a general model of document content representation and concludes that the library profession needs to address the development of databank design models, relevance feedback methods and automatic indexing assessment methods, to make indexing more effective
  14. Magennis, M.: Expert rule-based query expansion (1995) 0.01
    0.009529176 = product of:
      0.019058352 = sum of:
        0.019058352 = product of:
          0.038116705 = sum of:
            0.038116705 = weight(_text_:systems in 5181) [ClassicSimilarity], result of:
              0.038116705 = score(doc=5181,freq=2.0), product of:
                0.16037072 = queryWeight, product of:
                  3.0731742 = idf(docFreq=5561, maxDocs=44218)
                  0.052184064 = queryNorm
                0.23767869 = fieldWeight in 5181, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.0731742 = idf(docFreq=5561, maxDocs=44218)
                  0.0546875 = fieldNorm(doc=5181)
          0.5 = coord(1/2)
      0.5 = coord(1/2)
    
    Abstract
    Examines how, for term based free text retrieval, Interactive Query Expansion (IQE) provides better retrieval performance tahn Automatic Query Expansion (AQE) but the performance of IQE depends on the strategy employed by the user to select expansion terms. The aim is to build an expert query expansion system using term selection rules based on expert users' strategies. It is expected that such a system will achieve better performance for novice or inexperienced users that either AQE or IQE. The procedure is to discover expert IQE users' term selection strategies through observation and interrogation, to construct a rule based query expansion (RQE) system based on these and to compare the resulting retrieval performance with that of comparable AQE and IQE systems
  15. Oard, D.W.: Alternative approaches for cross-language text retrieval (1997) 0.01
    0.009529176 = product of:
      0.019058352 = sum of:
        0.019058352 = product of:
          0.038116705 = sum of:
            0.038116705 = weight(_text_:systems in 1164) [ClassicSimilarity], result of:
              0.038116705 = score(doc=1164,freq=8.0), product of:
                0.16037072 = queryWeight, product of:
                  3.0731742 = idf(docFreq=5561, maxDocs=44218)
                  0.052184064 = queryNorm
                0.23767869 = fieldWeight in 1164, product of:
                  2.828427 = tf(freq=8.0), with freq of:
                    8.0 = termFreq=8.0
                  3.0731742 = idf(docFreq=5561, maxDocs=44218)
                  0.02734375 = fieldNorm(doc=1164)
          0.5 = coord(1/2)
      0.5 = coord(1/2)
    
    Abstract
    The explosive growth of the Internet and other sources of networked information have made automatic mediation of access to networked information sources an increasingly important problem. Much of this information is expressed as electronic text, and it is becoming practical to automatically convert some printed documents and recorded speech to electronic text as well. Thus, automated systems capable of detecting useful documents are finding widespread application. With even a small number of languages it can be inconvenient to issue the same query repeatedly in every language, so users who are able to read more than one language will likely prefer a multilingual text retrieval system over a collection of monolingual systems. And since reading ability in a language does not always imply fluent writing ability in that language, such users will likely find cross-language text retrieval particularly useful for languages in which they are less confident of their ability to express their information needs effectively. The use of such systems can be also be beneficial if the user is able to read only a single language. For example, when only a small portion of the document collection will ever be examined by the user, performing retrieval before translation can be significantly more economical than performing translation before retrieval. So when the application is sufficiently important to justify the time and effort required for translation, those costs can be minimized if an effective cross-language text retrieval system is available. Even when translation is not available, there are circumstances in which cross-language text retrieval could be useful to a monolingual user. For example, a researcher might find a paper published in an unfamiliar language useful if that paper contains references to works by the same author that are in the researcher's native language.
    Multilingual text retrieval can be defined as selection of useful documents from collections that may contain several languages (English, French, Chinese, etc.). This formulation allows for the possibility that individual documents might contain more than one language, a common occurrence in some applications. Both cross-language and within-language retrieval are included in this formulation, but it is the cross-language aspect of the problem which distinguishes multilingual text retrieval from its well studied monolingual counterpart. At the SIGIR 96 workshop on "Cross-Linguistic Information Retrieval" the participants discussed the proliferation of terminology being used to describe the field and settled on "Cross-Language" as the best single description of the salient aspect of the problem. "Multilingual" was felt to be too broad, since that term has also been used to describe systems able to perform within-language retrieval in more than one language but that lack any cross-language capability. "Cross-lingual" and "cross-linguistic" were felt to be equally good descriptions of the field, but "crosslanguage" was selected as the preferred term in the interest of standardization. Unfortunately, at about the same time the U.S. Defense Advanced Research Projects Agency (DARPA) introduced "translingual" as their preferred term, so we are still some distance from reaching consensus on this matter.
  16. Hemmje, M.: LyberWorld - a 3D graphical user interface for fulltext retrieval (1995) 0.01
    0.009529176 = product of:
      0.019058352 = sum of:
        0.019058352 = product of:
          0.038116705 = sum of:
            0.038116705 = weight(_text_:systems in 2385) [ClassicSimilarity], result of:
              0.038116705 = score(doc=2385,freq=2.0), product of:
                0.16037072 = queryWeight, product of:
                  3.0731742 = idf(docFreq=5561, maxDocs=44218)
                  0.052184064 = queryNorm
                0.23767869 = fieldWeight in 2385, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.0731742 = idf(docFreq=5561, maxDocs=44218)
                  0.0546875 = fieldNorm(doc=2385)
          0.5 = coord(1/2)
      0.5 = coord(1/2)
    
    Source
    Proceeding CHI '95 Conference Companion on Human Factors in Computing Systems
  17. Efthimiadis, E.N.: User choices : a new yardstick for the evaluation of ranking algorithms for interactive query expansion (1995) 0.01
    0.008837775 = product of:
      0.01767555 = sum of:
        0.01767555 = product of:
          0.0353511 = sum of:
            0.0353511 = weight(_text_:22 in 5697) [ClassicSimilarity], result of:
              0.0353511 = score(doc=5697,freq=2.0), product of:
                0.1827397 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.052184064 = queryNorm
                0.19345059 = fieldWeight in 5697, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=5697)
          0.5 = coord(1/2)
      0.5 = coord(1/2)
    
    Date
    22. 2.1996 13:14:10
  18. Fidel, R.; Efthimiadis, E.N.: Terminological knowledge structure for intermediary expert systems (1995) 0.01
    0.008167865 = product of:
      0.01633573 = sum of:
        0.01633573 = product of:
          0.03267146 = sum of:
            0.03267146 = weight(_text_:systems in 5695) [ClassicSimilarity], result of:
              0.03267146 = score(doc=5695,freq=2.0), product of:
                0.16037072 = queryWeight, product of:
                  3.0731742 = idf(docFreq=5561, maxDocs=44218)
                  0.052184064 = queryNorm
                0.2037246 = fieldWeight in 5695, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.0731742 = idf(docFreq=5561, maxDocs=44218)
                  0.046875 = fieldNorm(doc=5695)
          0.5 = coord(1/2)
      0.5 = coord(1/2)
    
  19. Kwok, K.L.: ¬A network approach to probabilistic information retrieval (1995) 0.01
    0.008167865 = product of:
      0.01633573 = sum of:
        0.01633573 = product of:
          0.03267146 = sum of:
            0.03267146 = weight(_text_:systems in 5696) [ClassicSimilarity], result of:
              0.03267146 = score(doc=5696,freq=2.0), product of:
                0.16037072 = queryWeight, product of:
                  3.0731742 = idf(docFreq=5561, maxDocs=44218)
                  0.052184064 = queryNorm
                0.2037246 = fieldWeight in 5696, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.0731742 = idf(docFreq=5561, maxDocs=44218)
                  0.046875 = fieldNorm(doc=5696)
          0.5 = coord(1/2)
      0.5 = coord(1/2)
    
    Source
    ACM transactions on information systems. 13(1995) no.3, S.324-353
  20. Schwartz, C.: Web search engines (1998) 0.01
    0.008167865 = product of:
      0.01633573 = sum of:
        0.01633573 = product of:
          0.03267146 = sum of:
            0.03267146 = weight(_text_:systems in 5700) [ClassicSimilarity], result of:
              0.03267146 = score(doc=5700,freq=2.0), product of:
                0.16037072 = queryWeight, product of:
                  3.0731742 = idf(docFreq=5561, maxDocs=44218)
                  0.052184064 = queryNorm
                0.2037246 = fieldWeight in 5700, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.0731742 = idf(docFreq=5561, maxDocs=44218)
                  0.046875 = fieldNorm(doc=5700)
          0.5 = coord(1/2)
      0.5 = coord(1/2)
    
    Abstract
    This reviews looks briefly at the history of WWW search engine development, considers the current state of affairs, and reflects on the future. Networked discovery tools have evolved along with Internet resource availability. WWW search engines display some complexity in their variety, content, resource acquisition strategies, and in the array of tools the deploy to assist users. A small but growing body of evaluation literature, much of it not systematic in nature, indicates that performance effectiveness is difficult to assess in this setting. Significant improvements in general-content search engine retrieval and ranking performance may not be possible, and are probalby not worth the effort, although search engine providers have introduced some rudimentary attempts at personalization, summarization, and query expansion. The shift to distributed search across multitype database systems could extend general networked discovery and retrieval to include smaller resource collections with rich metadata and navigation tools