Search (5 results, page 1 of 1)

0.05040447 = product of:
  0.075606704 = sum of:
    0.05889038 = weight(_text_:query in 2456) [ClassicSimilarity], result of:
      0.05889038 = score(doc=2456,freq=2.0), product of:
        0.22937049 = queryWeight, product of:
          4.6476326 = idf(docFreq=1151, maxDocs=44218)
          0.049352113 = queryNorm
        0.25674784 = fieldWeight in 2456, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          4.6476326 = idf(docFreq=1151, maxDocs=44218)
          0.0390625 = fieldNorm(doc=2456)
    0.016716326 = product of:
      0.03343265 = sum of:
        0.03343265 = weight(_text_:22 in 2456) [ClassicSimilarity], result of:
          0.03343265 = score(doc=2456,freq=2.0), product of:
            0.1728227 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.049352113 = queryNorm
            0.19345059 = fieldWeight in 2456, 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=2456)
      0.5 = coord(1/2)
  0.6666667 = coord(2/3)

Abstract

The use of non-English Web search engines has been prevalent. Given the popularity of Chinese Web searching and the unique characteristics of Chinese language, it is imperative to conduct studies with focuses on the analysis of Chinese Web search queries. In this paper, we report our research on the character usage of Chinese search logs from a Web search engine in Hong Kong. By examining the distribution of search query terms, we found that users tended to use more diversified terms and that the usage of characters in search queries was quite different from the character usage of general online information in Chinese. After studying the Zipf distribution of n-grams with different values of n, we found that the curve of unigram is the most curved one of all while the bigram curve follows the Zipf distribution best, and that the curves of n-grams with larger n (n = 3-6) had similar structures with ?-values in the range of 0.66-0.86. The distribution of combined n-grams was also studied. All the analyses are performed on the data both before and after the removal of function terms and incomplete terms and similar findings are revealed. We believe the findings from this study have provided some insights into further research in non-English Web searching and will assist in the design of more effective Chinese Web search engines.

Date

22.11.2008 17:57:22

0.039260253 = product of:
  0.11778076 = sum of:
    0.11778076 = weight(_text_:query in 336) [ClassicSimilarity], result of:
      0.11778076 = score(doc=336,freq=8.0), product of:
        0.22937049 = queryWeight, product of:
          4.6476326 = idf(docFreq=1151, maxDocs=44218)
          0.049352113 = queryNorm
        0.5134957 = fieldWeight in 336, product of:
          2.828427 = tf(freq=8.0), with freq of:
            8.0 = termFreq=8.0
          4.6476326 = idf(docFreq=1151, maxDocs=44218)
          0.0390625 = fieldNorm(doc=336)
  0.33333334 = coord(1/3)

Abstract

The number of non-English resources has been increasing rapidly on the Web. Although many studies have been conducted on the query logs in search engines that are primarily English-based (e.g., Excite and AltaVista), only a few of them have studied the information-seeking behavior on the Web in non-English languages. In this article, we report the analysis of the search-query logs of a search engine that focused on Chinese. Three months of search-query logs of Timway, a search engine based in Hong Kong, were collected and analyzed. Metrics on sessions, queries, search topics, and character usage are reported. N-gram analysis also has been applied to perform character-based analysis. Our analysis suggests that some characteristics identified in the search log, such as search topics and the mean number of queries per sessions, are similar to those in English search engines; however, other characteristics, such as the use of operators in query formulation, are significantly different. The analysis also shows that only a very small number of unique Chinese characters are used in search queries. We believe the findings from this study have provided some insights into further research in non-English Web searching.

0.027761191 = product of:
  0.08328357 = sum of:
    0.08328357 = weight(_text_:query in 4573) [ClassicSimilarity], result of:
      0.08328357 = score(doc=4573,freq=4.0), product of:
        0.22937049 = queryWeight, product of:
          4.6476326 = idf(docFreq=1151, maxDocs=44218)
          0.049352113 = queryNorm
        0.3630963 = fieldWeight in 4573, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          4.6476326 = idf(docFreq=1151, maxDocs=44218)
          0.0390625 = fieldNorm(doc=4573)
  0.33333334 = coord(1/3)

Abstract

A large number of studies have investigated the transaction log of general-purpose search engines such as Excite and AItaVista, but few studies have reported an the analysis of search logs for search engines that are limited to particular Web sites, namely, Web site search engines. In this article, we report our research an analyzing the search logs of the search engine of the Utah state government Web site. Our results show that some statistics, such as the number of search terms per query, of Web users are the same for general-purpose search engines and Web site search engines, but others, such as the search topics and the terms used, are considerably different. Possible reasons for the differences include the focused domain of Web site search engines and users' different information needs. The findings are useful for Web site developers to improve the performance of their services provided an the Web and for researchers to conduct further research in this area. The analysis also can be applied in e-government research by investigating how information should be delivered to users in government Web sites.

0.027761191 = product of:
  0.08328357 = sum of:
    0.08328357 = weight(_text_:query in 5054) [ClassicSimilarity], result of:
      0.08328357 = score(doc=5054,freq=4.0), product of:
        0.22937049 = queryWeight, product of:
          4.6476326 = idf(docFreq=1151, maxDocs=44218)
          0.049352113 = queryNorm
        0.3630963 = fieldWeight in 5054, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          4.6476326 = idf(docFreq=1151, maxDocs=44218)
          0.0390625 = fieldNorm(doc=5054)
  0.33333334 = coord(1/3)

Abstract

As increasing numbers of non-English resources have become available on the Web, the interesting and important issue of how Web users can retrieve documents in different languages has arisen. Cross-language information retrieval (CLIP), the study of retrieving information in one language by queries expressed in another language, is a promising approach to the problem. Cross-language information retrieval has attracted much attention in recent years. Most research systems have achieved satisfactory performance on standard Text REtrieval Conference (TREC) collections such as news articles, but CLIR techniques have not been widely studied and evaluated for applications such as Web portals. In this article, the authors present their research in developing and evaluating a multilingual English-Chinese Web portal that incorporates various CLIP techniques for use in the business domain. A dictionary-based approach was adopted and combines phrasal translation, co-occurrence analysis, and pre- and posttranslation query expansion. The portal was evaluated by domain experts, using a set of queries in both English and Chinese. The experimental results showed that co-occurrence-based phrasal translation achieved a 74.6% improvement in precision over simple word-byword translation. When used together, pre- and posttranslation query expansion improved the performance slightly, achieving a 78.0% improvement over the baseline word-by-word translation approach. In general, applying CLIR techniques in Web applications shows promise.

0.024056775 = product of:
  0.072170325 = sum of:
    0.072170325 = product of:
      0.14434065 = sum of:
        0.14434065 = weight(_text_:page in 4242) [ClassicSimilarity], result of:
          0.14434065 = score(doc=4242,freq=4.0), product of:
            0.27565226 = queryWeight, product of:
              5.5854197 = idf(docFreq=450, maxDocs=44218)
              0.049352113 = queryNorm
            0.5236331 = fieldWeight in 4242, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              5.5854197 = idf(docFreq=450, maxDocs=44218)
              0.046875 = fieldNorm(doc=4242)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)

Abstract

With more than two billion pages created by millions of Web page authors and organizations, the World Wide Web is a tremendously rich knowledge base. The knowledge comes not only from the content of the pages themselves, but also from the unique characteristics of the Web, such as its hyperlink structure and its diversity of content and languages. Analysis of these characteristics often reveals interesting patterns and new knowledge. Such knowledge can be used to improve users' efficiency and effectiveness in searching for information an the Web, and also for applications unrelated to the Web, such as support for decision making or business management. The Web's size and its unstructured and dynamic content, as well as its multilingual nature, make the extraction of useful knowledge a challenging research problem. Furthermore, the Web generates a large amount of data in other formats that contain valuable information. For example, Web server logs' information about user access patterns can be used for information personalization or improving Web page design.