Search (4 results, page 1 of 1)

0.016672583 = product of:
  0.033345167 = sum of:
    0.033345167 = product of:
      0.06669033 = sum of:
        0.06669033 = weight(_text_:systems in 0) [ClassicSimilarity], result of:
          0.06669033 = score(doc=0,freq=12.0), product of:
            0.16037072 = queryWeight, product of:
              3.0731742 = idf(docFreq=5561, maxDocs=44218)
              0.052184064 = queryNorm
            0.41585106 = fieldWeight in 0, product of:
              3.4641016 = tf(freq=12.0), with freq of:
                12.0 = termFreq=12.0
              3.0731742 = idf(docFreq=5561, maxDocs=44218)
              0.0390625 = fieldNorm(doc=0)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

As information becomes more ubiquitous and the demands that searchers have on search systems grow, there is a need to support search behaviors beyond simple lookup. Information seeking is the process or activity of attempting to obtain information in both human and technological contexts. Exploratory search describes an information-seeking problem context that is open-ended, persistent, and multifaceted, and information-seeking processes that are opportunistic, iterative, and multitactical. Exploratory searchers aim to solve complex problems and develop enhanced mental capacities. Exploratory search systems support this through symbiotic human-machine relationships that provide guidance in exploring unfamiliar information landscapes. Exploratory search has gained prominence in recent years. There is an increased interest from the information retrieval, information science, and human-computer interaction communities in moving beyond the traditional turn-taking interaction model supported by major Web search engines, and toward support for human intelligence amplification and information use. In this lecture, we introduce exploratory search, relate it to relevant extant research, outline the features of exploratory search systems, discuss the evaluation of these systems, and suggest some future directions for supporting exploratory search. Exploratory search is a new frontier in the search domain and is becoming increasingly important in shaping our future world.

Content

Table of Contents: Introduction / Defining Exploratory Search / Related Work / Features of Exploratory Search Systems / Evaluation of Exploratory Search Systems / Future Directions and concluding Remarks

0.007700737 = product of:
  0.015401474 = sum of:
    0.015401474 = product of:
      0.030802948 = sum of:
        0.030802948 = weight(_text_:systems in 1486) [ClassicSimilarity], result of:
          0.030802948 = score(doc=1486,freq=4.0), product of:
            0.16037072 = queryWeight, product of:
              3.0731742 = idf(docFreq=5561, maxDocs=44218)
              0.052184064 = queryNorm
            0.19207339 = fieldWeight in 1486, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              3.0731742 = idf(docFreq=5561, maxDocs=44218)
              0.03125 = fieldNorm(doc=1486)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

LCSH

Information storage and retrieval systems

Subject

Information storage and retrieval systems

0.0054452433 = product of:
  0.010890487 = sum of:
    0.010890487 = product of:
      0.021780973 = sum of:
        0.021780973 = weight(_text_:systems in 26) [ClassicSimilarity], result of:
          0.021780973 = score(doc=26,freq=2.0), product of:
            0.16037072 = queryWeight, product of:
              3.0731742 = idf(docFreq=5561, maxDocs=44218)
              0.052184064 = queryNorm
            0.1358164 = fieldWeight in 26, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.0731742 = idf(docFreq=5561, maxDocs=44218)
              0.03125 = fieldNorm(doc=26)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

We live in an information age that requires us, more than ever, to represent, access, and use information. Over the last several decades, we have developed a modern science and technology for information retrieval, relentlessly pursuing the vision of a "memex" that Vannevar Bush proposed in his seminal article, "As We May Think." Faceted search plays a key role in this program. Faceted search addresses weaknesses of conventional search approaches and has emerged as a foundation for interactive information retrieval. User studies demonstrate that faceted search provides more effective information-seeking support to users than best-first search. Indeed, faceted search has become increasingly prevalent in online information access systems, particularly for e-commerce and site search. In this lecture, we explore the history, theory, and practice of faceted search. Although we cannot hope to be exhaustive, our aim is to provide sufficient depth and breadth to offer a useful resource to both researchers and practitioners. Because faceted search is an area of interest to computer scientists, information scientists, interface designers, and usability researchers, we do not assume that the reader is a specialist in any of these fields. Rather, we offer a self-contained treatment of the topic, with an extensive bibliography for those who would like to pursue particular aspects in more depth.

0.0047157193 = product of:
  0.0094314385 = sum of:
    0.0094314385 = product of:
      0.018862877 = sum of:
        0.018862877 = weight(_text_:systems in 92) [ClassicSimilarity], result of:
          0.018862877 = score(doc=92,freq=6.0), product of:
            0.16037072 = queryWeight, product of:
              3.0731742 = idf(docFreq=5561, maxDocs=44218)
              0.052184064 = queryNorm
            0.11762045 = fieldWeight in 92, product of:
              2.4494898 = tf(freq=6.0), with freq of:
                6.0 = termFreq=6.0
              3.0731742 = idf(docFreq=5561, maxDocs=44218)
              0.015625 = fieldNorm(doc=92)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Content

Information representation and retrieval : an overview -- Information representation I : basic approaches -- Information representation II : related topics -- Language in information representation and retrieval -- Retrieval techniques and query representation -- Retrieval approaches -- Information retrieval models -- Information retrieval systems -- Retrieval of information unique in content or format -- The user dimension in information representation and retrieval -- Evaluation of information representation and retrieval -- Artificial intelligence in information representation and retrieval.

LCSH

Information storage and retrieval systems

Subject

Information storage and retrieval systems