Interfacing thought: cognitive aspects of human-computer interaction
Query expansion using local and global document analysis
SIGIR '96 Proceedings of the 19th annual international ACM SIGIR conference on Research and development in information retrieval
A vector space model for automatic indexing
Communications of the ACM
An information-theoretic approach to automatic query expansion
ACM Transactions on Information Systems (TOIS)
A Comparative Study on Feature Selection in Text Categorization
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
Accurate methods for the statistics of surprise and coincidence
Computational Linguistics - Special issue on using large corpora: I
Mining rich session context to improve web search
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
| Hi-index | 0.01 |
Mining user's search context promises major improvements in several key aspects of Web search. Usage information such as search click-through has been a valuable source of information to determine what users want. However, such server side information is limited to query and corresponding clicks. Such query logs often do not contain sufficient information to determine user's search intent. Therefore, it is important to capture user's other activities such as the documents read or URLs opened before submitting a query. In this paper, we propose a framework to capture information about client side activities and share them with Web search engine effectively using Proxy server. From extensive experiments based on real user's experience, it is evident that user's search needs are influenced by the user's Desktop and Web activities. From further analysis, we observe that with an overhead of 2.32ms Proxy server can extract and send the additional information to a Web search engine along with a user's search request.