Search (3 results, page 1 of 1)

0.0012685166 = product of:
  0.008879616 = sum of:
    0.008879616 = product of:
      0.044398077 = sum of:
        0.044398077 = weight(_text_:retrieval in 2586) [ClassicSimilarity], result of:
          0.044398077 = score(doc=2586,freq=6.0), product of:
            0.109568894 = queryWeight, product of:
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.03622214 = queryNorm
            0.40520695 = fieldWeight in 2586, product of:
              2.4494898 = tf(freq=6.0), with freq of:
                6.0 = termFreq=6.0
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.0546875 = fieldNorm(doc=2586)
      0.2 = coord(1/5)
  0.14285715 = coord(1/7)

Abstract

Hierarchic document clustering has been widely applied to information retrieval (IR) on the grounds of its potential improved effectiveness over inverted file search (IFS). However, previous research has been inconclusive as to whether clustering does bring improvements. In this paper we take the view that if hierarchic clustering is applied to search results (query-specific clustering), then it has the potential to increase the retrieval effectiveness compared both to that of static clustering and of conventional IFS. We conducted a number of experiments using five document collections and four hierarchic clustering methods. Our results show that the effectiveness of query-specific clustering is indeed higher, and suggest that there is scope for its application to IR.

8.877766E-4 = product of:
  0.006214436 = sum of:
    0.006214436 = product of:
      0.03107218 = sum of:
        0.03107218 = weight(_text_:retrieval in 2731) [ClassicSimilarity], result of:
          0.03107218 = score(doc=2731,freq=4.0), product of:
            0.109568894 = queryWeight, product of:
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.03622214 = queryNorm
            0.2835858 = fieldWeight in 2731, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.046875 = fieldNorm(doc=2731)
      0.2 = coord(1/5)
  0.14285715 = coord(1/7)

Abstract

Summarisation is traditionally used to produce summaries of the textual contents of documents. In this paper, it is argued that summarisation methods can also be applied to the logical structure of XML documents. Structure summarisation selects the most important elements of the logical structure and ensures that the user's attention is focused towards sections, subsections, etc. that are believed to be of particular interest. Structure summaries are shown to users as hierarchical tables of contents. This paper discusses methods for structure summarisation that use various features of XML elements in order to select document portions that a user's attention should be focused to. An evaluation methodology for structure summarisation is also introduced and summarisation results using various summariser versions are presented and compared to one another. We show that data sets used in information retrieval evaluation can be used effectively in order to produce high quality (query independent) structure summaries. We also discuss the choice and effectiveness of particular summariser features with respect to several evaluation measures.

Content

Beitrag in einem Themenheft "Large-Scale and Distributed Systems for Information Retrieval" Vgl.: doi:10.1016/j.ipm.2011.11.002.

5.2312744E-4 = product of:
  0.003661892 = sum of:
    0.003661892 = product of:
      0.01830946 = sum of:
        0.01830946 = weight(_text_:retrieval in 4989) [ClassicSimilarity], result of:
          0.01830946 = score(doc=4989,freq=2.0), product of:
            0.109568894 = queryWeight, product of:
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.03622214 = queryNorm
            0.16710453 = fieldWeight in 4989, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.0390625 = fieldNorm(doc=4989)
      0.2 = coord(1/5)
  0.14285715 = coord(1/7)

Abstract

Understanding search behavior is important and leads to more effective interfaces that support searchers throughout the search process. In this article, through an observational user study, we investigate the search behavior of 15 visually impaired and 15 sighted searchers while they complete complex search tasks online. We study complex search tasks because they are challenging, cognitively intensive and affect performance of searchers. We compare the behavior of the two groups of searchers at four stages of the information-seeking process namely, Query Formulation, Search Results Exploration, Query Reformulation, and Search Results Management. For each stage, we identify research questions to investigate the impact of speech-based screen readers on the information-seeking behavior of visually impaired users. Significant differences were observed during query formulation and in the use of query-level support features such as query suggestions and spelling suggestions. In addition, screen-reader users submitted a lower number of queries and displayed comparatively limited exploratory behavior during search results exploration. We investigate how a lack of visual cues affected visually impaired searchers' approach towards query reformulation and observed different strategies to manage and use information encountered during the search process. We discuss the implications that our findings have for the design of search interfaces and propose a set of design guidelines to consider when designing interfaces that are usable and accessible with screen readers. This work also enhances our understanding of search behavior when using an auditory interface and could be useful when designing audio-based information retrieval systems.