Log mining to support web query expansions
Log mining to support web query expansions
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DOI：
10.1109/icinfa.2009.5204952
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发表时间：
2009-06
期刊：
影响因子：
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通讯作者：
Patrick Ngok;Zhiguo Gong
中科院分区：
文献类型：
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作者：
Patrick Ngok;Zhiguo Gong
本文通过挖掘查询日志中的查询信息来实现查询扩展。利用数据挖掘关联技术建立关联关系。然后将每个新的查询与新建立的关联规则进行比较，并利用原始查询和新添加的项目构造新的扩展查询。此外，查询日志中的其他信息也将被处理，以实现查询扩展。然后对原始查询、通过关联扩展的查询和通过查询信息扩展的查询进行性能评价比较。实验表明，新扩展的查询可以产生更好的Web查询搜索性能。
In this paper, query expansion will be achieved by mining query information in a query log. An association will be constructed by data mining association technique. Then every incoming new query will be compared with the newly built association rule, and a new expanded query can be constructed with the original query and the newly added item. In addition, other information in the query log will also be processed to achieve query expansion. Then a performance evaluation comparison will be done among the original query, query expanded by association, and query expanded by query information. The experiment shows that the newly expanded query can produce better performance for web query searching.