Search (2 results, page 1 of 1)

  • × theme_ss:"Suchtaktik"
  • × author_ss:"Wolfram, D."
  1. Wolfram, D.: Search characteristics in different types of Web-based IR environments : are they the same? (2008) 0.05
    0.049510203 = product of:
      0.1485306 = sum of:
        0.1485306 = weight(_text_:search in 2093) [ClassicSimilarity], result of:
          0.1485306 = score(doc=2093,freq=20.0), product of:
            0.1747324 = queryWeight, product of:
              3.475677 = idf(docFreq=3718, maxDocs=44218)
              0.05027291 = queryNorm
            0.8500461 = fieldWeight in 2093, product of:
              4.472136 = tf(freq=20.0), with freq of:
                20.0 = termFreq=20.0
              3.475677 = idf(docFreq=3718, maxDocs=44218)
              0.0546875 = fieldNorm(doc=2093)
      0.33333334 = coord(1/3)
    
    Abstract
    Transaction logs from four different Web-based information retrieval environments (bibliographic databank, OPAC, search engine, specialized search system) were analyzed for empirical regularities in search characteristics to determine whether users engage in different behaviors in different Web-based search environments. Descriptive statistics and relative frequency distributions related to term usage, query formulation, and session duration were tabulated. The analysis revealed that there are differences in these characteristics. Users were more likely to engage in extensive searching using the OPAC and specialized search system. Surprisingly, the bibliographic databank search environment resulted in the most parsimonious searching, more similar to a general search engine. Although on the surface Web-based search facilities may appear similar, users do engage in different search behaviors.
  2. Zhang, J.; Wolfram, D.; Wang, P.: Analysis of query keywords of sports-related queries using visualization and clustering (2009) 0.02
    0.019369897 = product of:
      0.058109686 = sum of:
        0.058109686 = weight(_text_:search in 2947) [ClassicSimilarity], result of:
          0.058109686 = score(doc=2947,freq=6.0), product of:
            0.1747324 = queryWeight, product of:
              3.475677 = idf(docFreq=3718, maxDocs=44218)
              0.05027291 = queryNorm
            0.33256388 = fieldWeight in 2947, product of:
              2.4494898 = tf(freq=6.0), with freq of:
                6.0 = termFreq=6.0
              3.475677 = idf(docFreq=3718, maxDocs=44218)
              0.0390625 = fieldNorm(doc=2947)
      0.33333334 = coord(1/3)
    
    Abstract
    The authors investigated 11 sports-related query keywords extracted from a public search engine query log to better understand sports-related information seeking on the Internet. After the query log contents were cleaned and query data were parsed, popular sports-related keywords were identified, along with frequently co-occurring query terms associated with the identified keywords. Relationships among each sports-related focus keyword and its related keywords were characterized and grouped using multidimensional scaling (MDS) in combination with traditional hierarchical clustering methods. The two approaches were synthesized in a visual context by highlighting the results of the hierarchical clustering analysis in the visual MDS configuration. Important events, people, subjects, merchandise, and so on related to a sport were illustrated, and relationships among the sports were analyzed. A small-scale comparative study of sports searches with and without term assistance was conducted. Searches that used search term assistance by relying on previous query term relationships outperformed the searches without the search term assistance. The findings of this study provide insights into sports information seeking behavior on the Internet. The developed method also may be applied to other query log subject areas.

Authors