Читать книгу Computational Analysis and Deep Learning for Medical Care - Группа авторов - Страница 34

Query suggestion enables the user to scrutinize a query with a single click; this became one of the most fundamental features of web search engines. In general, it is not clear when the user would turn to query suggestion; it depends on circumstances. In order to investigate when and how the user uses query suggestion, we analyzed three kinds of datasets obtained from a major commercial web search engine, comprising approximately 126 million unique queries, 876 million query suggestions, and 306 million action patterns of users. The analysis shows that query suggestion is often used.

1 When the original query is a rare query [8].

2 When the original query is a single-term query,

3 When query suggestions are unambiguous,

4 When query suggestions are generalizations or error corrections of the original query, and

5 After the user has clicked on several URLs in the first search result page.

The search engines are working to provide better query suggestion input, and that they should dynamically provide query suggestions according to the user’s current state. There are different types of approaches for keyword query suggestion. This can be classified into three categories: random walk–based, cluster-based, and learning to rank approaches. We briefly review the other methods from our observation; any of the given methods cannot consider the user location in query suggestion.