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Web Search Behavior Analysis Based on the Self-bundling Query Method

웹검색 행태 연구 - 사용자가 스스로 쿼리를 뭉치는 방법으로 -

  • 이중식 (서울대학교 융합과학기술대학원 차세대융합기술연구원)
  • Received : 2011.04.15
  • Accepted : 2011.05.13
  • Published : 2011.05.30

Abstract

Web search behavior has evolved. People now search using many diverse information devices in various situations. To monitor these scattered and shifting search patterns, an improved way of learning and analysis are needed. Traditional web search studies relied on the server transaction logs and single query instance analysis. Since people use multiple smart devices and their searching occurs intermittently through a day, a bundled query research could look at the whole context as well as penetrating search needs. To observe and analyze bundled queries, we developed a proprietary research software set including a log catcher, query bundling tool, and bundle monitoring tool. In this system, users' daily search logs are sent to our analytic server, every night the users need to log on our bundling tool to package his/her queries, a built in web survey collects additional data, and our researcher performs deep interviews on a weekly basis. Out of 90 participants in the study, it was found that a normal user generates on average 4.75 query bundles a day, and each bundle contains 2.75 queries. Query bundles were categorized by; Query refinement vs. Topic refinement and 9 different sub-categories.

Keywords

Web Search;Bundled Query;Session;RTA;Categorization

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