Search (10 results, page 1 of 1)

  • × theme_ss:"Semantisches Umfeld in Indexierung u. Retrieval"
  • × type_ss:"el"
  1. Jansen, B.; Browne, G.M.: Navigating information spaces : index / mind map / topic map? (2021) 0.03
    0.031811368 = product of:
      0.12724547 = sum of:
        0.12724547 = weight(_text_:architecture in 436) [ClassicSimilarity], result of:
          0.12724547 = score(doc=436,freq=2.0), product of:
            0.26485988 = queryWeight, product of:
              5.4353957 = idf(docFreq=523, maxDocs=44218)
              0.048728723 = queryNorm
            0.48042563 = fieldWeight in 436, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              5.4353957 = idf(docFreq=523, maxDocs=44218)
              0.0625 = fieldNorm(doc=436)
      0.25 = coord(1/4)
    
    Abstract
    This paper discusses the use of wiki technology to provide a navigation structure for a collection of newspaper clippings. We overview the architecture of the wiki, discuss the navigation structure and pose the question: is the navigation structure an index, and if so, what type, or is it just a linkage structure or topic map. Does such a distinction really matter? Are these definitions in reality function based?
  2. Tudhope, D.; Alani, H.; Jones, C.: Augmenting thesaurus relationships : possibilities for retrieval (2001) 0.02
    0.020323653 = product of:
      0.08129461 = sum of:
        0.08129461 = product of:
          0.16258922 = sum of:
            0.16258922 = weight(_text_:thesaurus in 1520) [ClassicSimilarity], result of:
              0.16258922 = score(doc=1520,freq=16.0), product of:
                0.22517926 = queryWeight, product of:
                  4.6210785 = idf(docFreq=1182, maxDocs=44218)
                  0.048728723 = queryNorm
                0.7220435 = fieldWeight in 1520, product of:
                  4.0 = tf(freq=16.0), with freq of:
                    16.0 = termFreq=16.0
                  4.6210785 = idf(docFreq=1182, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=1520)
          0.5 = coord(1/2)
      0.25 = coord(1/4)
    
    Abstract
    This paper discusses issues concerning the augmentation of thesaurus relationships, in light of new application possibilities for retrieval. We first discuss a case study that explored the retrieval potential of an augmented set of thesaurus relationships by specialising standard relationships into richer subtypes, in particular hierarchical geographical containment and the associative relationship. We then locate this work in a broader context by reviewing various attempts to build taxonomies of thesaurus relationships, and conclude by discussing the feasibility of hierarchically augmenting the core set of thesaurus relationships, particularly the associative relationship. We discuss the possibility of enriching the specification and semantics of Related Term (RT relationships), while maintaining compatibility with traditional thesauri via a limited hierarchical extension of the associative (and hierarchical) relationships. This would be facilitated by distinguishing the type of term from the (sub)type of relationship and explicitly specifying semantic categories for terms following a faceted approach. We first illustrate how hierarchical spatial relationships can be used to provide more flexible retrieval for queries incorporating place names in applications employing online gazetteers and geographical thesauri. We then employ a set of experimental scenarios to investigate key issues affecting use of the associative (RT) thesaurus relationships in semantic distance measures. Previous work has noted the potential of RTs in thesaurus search aids but also the problem of uncontrolled expansion of query term sets. Results presented in this paper suggest the potential for taking account of the hierarchical context of an RT link and specialisations of the RT relationship
    Theme
    Konzeption und Anwendung des Prinzips Thesaurus
  3. Michel, D.: Taxonomy of Subject Relationships (1997) 0.01
    0.014370992 = product of:
      0.057483967 = sum of:
        0.057483967 = product of:
          0.114967935 = sum of:
            0.114967935 = weight(_text_:thesaurus in 5346) [ClassicSimilarity], result of:
              0.114967935 = score(doc=5346,freq=2.0), product of:
                0.22517926 = queryWeight, product of:
                  4.6210785 = idf(docFreq=1182, maxDocs=44218)
                  0.048728723 = queryNorm
                0.5105618 = fieldWeight in 5346, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  4.6210785 = idf(docFreq=1182, maxDocs=44218)
                  0.078125 = fieldNorm(doc=5346)
          0.5 = coord(1/2)
      0.25 = coord(1/4)
    
    Theme
    Konzeption und Anwendung des Prinzips Thesaurus
  4. Zhang, J.; Mostafa, J.; Tripathy, H.: Information retrieval by semantic analysis and visualization of the concept space of D-Lib® magazine (2002) 0.01
    0.011915798 = product of:
      0.047663193 = sum of:
        0.047663193 = product of:
          0.09532639 = sum of:
            0.09532639 = weight(_text_:thesaurus in 1211) [ClassicSimilarity], result of:
              0.09532639 = score(doc=1211,freq=22.0), product of:
                0.22517926 = queryWeight, product of:
                  4.6210785 = idf(docFreq=1182, maxDocs=44218)
                  0.048728723 = queryNorm
                0.42333555 = fieldWeight in 1211, product of:
                  4.690416 = tf(freq=22.0), with freq of:
                    22.0 = termFreq=22.0
                  4.6210785 = idf(docFreq=1182, maxDocs=44218)
                  0.01953125 = fieldNorm(doc=1211)
          0.5 = coord(1/2)
      0.25 = coord(1/4)
    
    Abstract
    From the user's perspective, however, it is still difficult to use current information retrieval systems. Users frequently have problems expressing their information needs and translating those needs into queries. This is partly due to the fact that information needs cannot be expressed appropriately in systems terms. It is not unusual for users to input search terms that are different from the index terms information systems use. Various methods have been proposed to help users choose search terms and articulate queries. One widely used approach is to incorporate into the information system a thesaurus-like component that represents both the important concepts in a particular subject area and the semantic relationships among those concepts. Unfortunately, the development and use of thesauri is not without its own problems. The thesaurus employed in a specific information system has often been developed for a general subject area and needs significant enhancement to be tailored to the information system where it is to be used. This thesaurus development process, if done manually, is both time consuming and labor intensive. Usage of a thesaurus in searching is complex and may raise barriers for the user. For illustration purposes, let us consider two scenarios of thesaurus usage. In the first scenario the user inputs a search term and the thesaurus then displays a matching set of related terms. Without an overview of the thesaurus - and without the ability to see the matching terms in the context of other terms - it may be difficult to assess the quality of the related terms in order to select the correct term. In the second scenario the user browses the whole thesaurus, which is organized as in an alphabetically ordered list. The problem with this approach is that the list may be long, and neither does it show users the global semantic relationship among all the listed terms.
    Nevertheless, because thesaurus use has shown to improve retrieval, for our method we integrate functions in the search interface that permit users to explore built-in search vocabularies to improve retrieval from digital libraries. Our method automatically generates the terms and their semantic relationships representing relevant topics covered in a digital library. We call these generated terms the "concepts", and the generated terms and their semantic relationships we call the "concept space". Additionally, we used a visualization technique to display the concept space and allow users to interact with this space. The automatically generated term set is considered to be more representative of subject area in a corpus than an "externally" imposed thesaurus, and our method has the potential of saving a significant amount of time and labor for those who have been manually creating thesauri as well. Information visualization is an emerging discipline and developed very quickly in the last decade. With growing volumes of documents and associated complexities, information visualization has become increasingly important. Researchers have found information visualization to be an effective way to use and understand information while minimizing a user's cognitive load. Our work was based on an algorithmic approach of concept discovery and association. Concepts are discovered using an algorithm based on an automated thesaurus generation procedure. Subsequently, similarities among terms are computed using the cosine measure, and the associations among terms are established using a method known as max-min distance clustering. The concept space is then visualized in a spring embedding graph, which roughly shows the semantic relationships among concepts in a 2-D visual representation. The semantic space of the visualization is used as a medium for users to retrieve the desired documents. In the remainder of this article, we present our algorithmic approach of concept generation and clustering, followed by description of the visualization technique and interactive interface. The paper ends with key conclusions and discussions on future work.
  5. Landauer, T.K.; Foltz, P.W.; Laham, D.: ¬An introduction to Latent Semantic Analysis (1998) 0.01
    0.010071765 = product of:
      0.04028706 = sum of:
        0.04028706 = weight(_text_:26 in 1162) [ClassicSimilarity], result of:
          0.04028706 = score(doc=1162,freq=2.0), product of:
            0.17208664 = queryWeight, product of:
              3.5315237 = idf(docFreq=3516, maxDocs=44218)
              0.048728723 = queryNorm
            0.23410915 = fieldWeight in 1162, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5315237 = idf(docFreq=3516, maxDocs=44218)
              0.046875 = fieldNorm(doc=1162)
      0.25 = coord(1/4)
    
    Date
    27.12.2013 16:35:26
  6. Fowler, R.H.; Wilson, B.A.; Fowler, W.A.L.: Information navigator : an information system using associative networks for display and retrieval (1992) 0.01
    0.008622595 = product of:
      0.03449038 = sum of:
        0.03449038 = product of:
          0.06898076 = sum of:
            0.06898076 = weight(_text_:thesaurus in 919) [ClassicSimilarity], result of:
              0.06898076 = score(doc=919,freq=2.0), product of:
                0.22517926 = queryWeight, product of:
                  4.6210785 = idf(docFreq=1182, maxDocs=44218)
                  0.048728723 = queryNorm
                0.30633712 = fieldWeight in 919, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  4.6210785 = idf(docFreq=1182, maxDocs=44218)
                  0.046875 = fieldNorm(doc=919)
          0.5 = coord(1/2)
      0.25 = coord(1/4)
    
    Abstract
    Document retrieval is a highly interactive process dealing with large amounts of information. Visual representations can provide both a means for managing the complexity of large information structures and an interface style well suited to interactive manipulation. The system we have designed utilizes visually displayed graphic structures and a direct manipulation interface style to supply an integrated environment for retrieval. A common visually displayed network structure is used for query, document content, and term relations. A query can be modified through direct manipulation of its visual form by incorporating terms from any other information structure the system displays. An associative thesaurus of terms and an inter-document network provide information about a document collection that can complement other retrieval aids. Visualization of these large data structures makes use of fisheye views and overview diagrams to help overcome some of the inherent difficulties of orientation and navigation in large information structures.
  7. Knorz, G.; Rein, B.: Semantische Suche in einer Hochschulontologie : Ontologie-basiertes Information-Filtering und -Retrieval mit relationalen Datenbanken (2005) 0.01
    0.0057768105 = product of:
      0.023107242 = sum of:
        0.023107242 = product of:
          0.046214484 = sum of:
            0.046214484 = weight(_text_:22 in 4324) [ClassicSimilarity], result of:
              0.046214484 = score(doc=4324,freq=2.0), product of:
                0.17063968 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.048728723 = queryNorm
                0.2708308 = fieldWeight in 4324, 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=4324)
          0.5 = coord(1/2)
      0.25 = coord(1/4)
    
    Date
    11. 2.2011 18:22:25
  8. ALA / Subcommittee on Subject Relationships/Reference Structures: Final Report to the ALCTS/CCS Subject Analysis Committee (1997) 0.01
    0.0050298474 = product of:
      0.02011939 = sum of:
        0.02011939 = product of:
          0.04023878 = sum of:
            0.04023878 = weight(_text_:thesaurus in 1800) [ClassicSimilarity], result of:
              0.04023878 = score(doc=1800,freq=2.0), product of:
                0.22517926 = queryWeight, product of:
                  4.6210785 = idf(docFreq=1182, maxDocs=44218)
                  0.048728723 = queryNorm
                0.17869665 = fieldWeight in 1800, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  4.6210785 = idf(docFreq=1182, maxDocs=44218)
                  0.02734375 = fieldNorm(doc=1800)
          0.5 = coord(1/2)
      0.25 = coord(1/4)
    
    Theme
    Konzeption und Anwendung des Prinzips Thesaurus
  9. Bradford, R.B.: Relationship discovery in large text collections using Latent Semantic Indexing (2006) 0.00
    0.0033010344 = product of:
      0.013204138 = sum of:
        0.013204138 = product of:
          0.026408276 = sum of:
            0.026408276 = weight(_text_:22 in 1163) [ClassicSimilarity], result of:
              0.026408276 = score(doc=1163,freq=2.0), product of:
                0.17063968 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.048728723 = queryNorm
                0.15476047 = fieldWeight in 1163, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.03125 = fieldNorm(doc=1163)
          0.5 = coord(1/2)
      0.25 = coord(1/4)
    
    Source
    Proceedings of the Fourth Workshop on Link Analysis, Counterterrorism, and Security, SIAM Data Mining Conference, Bethesda, MD, 20-22 April, 2006. [http://www.siam.org/meetings/sdm06/workproceed/Link%20Analysis/15.pdf]
  10. Gillitzer, B.: Yewno (2017) 0.00
    0.0033010344 = product of:
      0.013204138 = sum of:
        0.013204138 = product of:
          0.026408276 = sum of:
            0.026408276 = weight(_text_:22 in 3447) [ClassicSimilarity], result of:
              0.026408276 = score(doc=3447,freq=2.0), product of:
                0.17063968 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.048728723 = queryNorm
                0.15476047 = fieldWeight in 3447, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.03125 = fieldNorm(doc=3447)
          0.5 = coord(1/2)
      0.25 = coord(1/4)
    
    Date
    22. 2.2017 10:16:49