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A Document Ranking Method With Query-Related Web Context
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DOI：10.1109/ACCESS.2019.2947166.png)
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摘要
En 中文
In this paper, an approach is proposed to evaluate and rearrange web pages, based on the query-related web context. The contexts we focus on are the terms co-occurring with queries in microblogs. The proposed approach is based on the retrieved result by a search engine. If a query is given, it retrieves the search results, and checks whether the query is on a burst state or not. If the query is on a burst state (or popular state), our method applies the query-related context to the search results. Since context terms can reflect the current interest of people regarding the query, a web page can be considered within the current interest of people, if it has many of the context terms. Thus, the retrieved web pages are re-ranked based on the context terms, to present the search result in accordance with the current public interest. We present some observations that show microblog contents and search queries are strongly related, if queries are on a burst state. In order to verify the effect of context terms, we conduct experiments, and compare the result with Google using a questionnaire survey.
Keyword:
Search engines
Google
Correlation
Twitter
Earthquakes
Web pages
Probabilistic logic
Query
document ranking
web context
microblogs
Google
Twitter
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期刊
IF:
3.6
论文数:
9.8W
被引数:
29.4W
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