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    <datestamp>2007-01-24</datestamp>
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    <type>article</type>
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    <creators>
      <item>
        <name>
          <family>Johnson</family>
          <given>D</given>
        </name>
        <id>dgjohnso@utas.edu.au</id>
      </item>
      <item>
        <name>
          <family>Malhotra</family>
          <given>V</given>
        </name>
        <id>vishv.malhotra@utas.edu.au</id>
      </item>
      <item>
        <name>
          <family>Vamplew</family>
          <given>P</given>
        </name>
        <id>p.vamplew@ballarat.edu.au</id>
      </item>
    </creators>
    <title>More Effective Web Search Using Bigrams and Trigrams</title>
    <ispublished>pub</ispublished>
    <for08>
      <item>080107</item>
    </for08>
    <subjects>
      <item>280103</item>
      <item>280105</item>
      <item>280205</item>
    </subjects>
    <full_text_status>public</full_text_status>
    <keywords>Web searching; Information need; Relevance feedback; Part-of-speech tagging</keywords>
    <note>Direct access to the article in journal available at http://www.webology.ir/2006/v3n4/a35.html</note>
    <suggestions>23/1 SvA: Couldn't get access to Romeo Sherpa to check, but figure as is available online not a problem! DOI not found. Checked Abstract and refs.</suggestions>
    <abstract>This paper investigates the effectiveness of quoted bigrams and trigrams as query terms to target web search. Prior research in this area has largely focused on static corpora each containing only a few million documents, and has reported mixed (usually negative) results. We investigate the bigram/trigram extraction problem and present an extraction algorithm that shows promising results when applied to real-time web search. We also present a prototype augmented search software package that can leverage the results provided by a web search engine to assist the web searcher identify important phrases and related documents quickly. This software has received favourable feedback in a recent user survey.</abstract>
    <date>2006</date>
    <date_type>published</date_type>
    <publication>Webology</publication>
    <volume>3</volume>
    <number>4</number>
    <pagerange>35</pagerange>
    <thesis_type>UNSPECIFIED</thesis_type>
    <refereed>TRUE</refereed>
    <issn>1735-188X</issn>
    <official_url>http://www.webology.ir/2006/v3n4/a35.html</official_url>
    <referencetext>Croft, W.B., Turtle, H.R., &amp; Lewis, D.D. (1991). The use of phrases and structured queries in information retrieval. In Proceedings of the 14th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, (pp 32-45). 
Internet Systems Consortium (2006). ISC Internet Domain Survey. Retrieved September 15, 2006, from http://www.isc.org/index.pl?/ops/ds/

Jansen, B. J., Spink, A., &amp; Saracevic, T. (2000). Real life, real users and real needs: A study and analysis of users' queries on the Web. Information Processing and Management, 36(2) (pp 207-227).

Jansen, J. (2006). AltaVista, AllTheWeb and Excite search engine query logs generously made available by Dr Jim Jansen. Retrieved September 15, 2006, from http://ist.psu.edu/faculty_pages/jjansen/

Justeson, J.S., &amp; Katz, S.M. (1995). Technical terminology: Some linguistic properties and an algorithm for identification in text. Natural Language Engineering, (pp. 9-27). Cambridge University Press.

Lewis, D.D., &amp; Croft, W.B. (1990). Term Clustering of Syntactic Phrases. Proceedings of the Thirteenth Annual International ACM SIGIR Conference on Research and Development in Information Retrieval.

Manning, C.D., &amp; Schutze, H. (2003a). Foundations of Statistical Natural Language Processing (sixth printing), (pp. 196-217). The MIT Press.

Manning, C.D., &amp; Schutze, H. (2003b). Foundations of Statistical Natural Language Processing (sixth printing), (pp. 29-34). The MIT Press.

MontyTagger (2006). The MontyLingua natural language package. Retrieved June 5, 2006, from http://web.media.mit.edu/~hugo/montylingua/index.html http://www.webology.ir/2006/v3n4/a35.html

QTag (2006). QTag probabilistic parts-of-speech tagger. Retrieved June 5, 2006, from http://www.english.bham.ac.uk/staff/omason/software/qtag.html

Rocchio, J. (1971). Relevance feedback in information retrieval. In Salton, G. (Ed.), The SMART Retrieval System: Experiments in Automatic Document Processing. Prentice-Hall, (pp. 313-323).

Silverstein, C., Henzinger, M., Marais, H., &amp; Moricz, M. (1999). Analysis of a very large web search engine query log. SIGIR Forum, 33(1), 6-12.

Spink, A. (2002). A user-centered approach to evaluating human interactions with web search engines: an exploratory study. Information Processing and Management , 38(3), 401-426.

The Stanford NLP Group Tagger (2006). The Stanford NLP Group Log-linear Part-Of-Speech Tagger. Retrieved June 5, 2006, from http://nlp.stanford.edu/software/tagger.shtml

Strzalkowski, T., &amp; Carballo, J.P. (1997). Natural Language Information Retrieval: TREC-4 Report. In Harman, D. (Ed.), Proceedings of the Fourth Text REtrieval Conference (TREC-4). Washington, D.C.

Sullivan, D. (2004). Search Engine Size Wars V Erupts. SearchEngineWatch, Retrieved on September 10, 2006, from http://blog.searchenginewatch.com/blog/041111-084221

TREC (2004). Robust Track: Robust test set. Retrieved from http://trec.nist.gov/data/t13_robust.html

TREC (2006). Text Retrieval Conference: Data - English Relevance Judgments. Retrieved August 8, 2006, from http://trec.nist.gov/data/reljudge_eng.html

Wikipedia (2006). "Mole disambiguation page". Retrieved September 1, 2006, from http://en.wikipedia.org/wiki/Mole</referencetext>
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