Query Categorization from Web Search Logs Using Machine Learning Algorithms
Christian Højgaard, Joachim Sejr, Yun-Gyung Cheong · International Journal of Database Theory and Application · 2016
This paper presents a data-driven methodology to disambiguate a query by suggesting relevant subcategories within a specific domain. This is achieved by finding correlations between the user’s search history and the context of the current search keyword. We apply automatic categorization on each query to identify a list of categories which can describe the query given. To predict the categories of a user input query, we employed machine learning algorithms. We present the preliminary evaluation results and conclude with future work.