Agglomerative clustering of a search engine query log
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Query clustering using user logs
ACM Transactions on Information Systems (TOIS)
Search engine coverage bias: evidence and possible causes
Information Processing and Management: an International Journal
A subjective measure of web search quality
Information Sciences—Informatics and Computer Science: An International Journal
Information Processing and Management: an International Journal - Special issue: Cross-language information retrieval
The impact of metadata implementation on webpage visibility in search engine results (part II)
Information Processing and Management: an International Journal - Special issue: Cross-language information retrieval
Click data as implicit relevance feedback in web search
Information Processing and Management: an International Journal
Query expansion with terms selected using lexical cohesion analysis of documents
Information Processing and Management: an International Journal
Information Processing and Management: an International Journal
A weight-based approach to information retrieval and relevance feedback
Expert Systems with Applications: An International Journal
Mining search engine query logs for social filtering-based query recommendation
Applied Soft Computing
An Effective Method for Chinese Related Queries Recommendation
SNPD '08 Proceedings of the 2008 Ninth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing
Personalized Concept-Based Clustering of Search Engine Queries
IEEE Transactions on Knowledge and Data Engineering
Learning latent semantic relations from clickthrough data for query suggestion
Proceedings of the 17th ACM conference on Information and knowledge management
Query Recommendation with TF-IQF Model and Popularity Factor
FSKD '08 Proceedings of the 2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 04
Frequent items in streaming data: An experimental evaluation of the state-of-the-art
Data & Knowledge Engineering
Automatic classification of Tamil documents using vector space model and artificial neural network
Expert Systems with Applications: An International Journal
Deriving Concept-Based User Profiles from Search Engine Logs
IEEE Transactions on Knowledge and Data Engineering
Knowledge-based vector space model for text clustering
Knowledge and Information Systems
Identifying frequent items in a network using gossip
Journal of Parallel and Distributed Computing
Expert Systems with Applications: An International Journal
A relational vector space model using an advanced weighting scheme for image retrieval
Information Processing and Management: an International Journal
Optimizing search engines results using linear programming
Expert Systems with Applications: An International Journal
The effect of user characteristics on search effectiveness in information retrieval
Information Processing and Management: an International Journal
A fuzzy decision support system for digital camera selection based on user preferences
Expert Systems with Applications: An International Journal
Generating suggestions for queries in the long tail with an inverted index
Information Processing and Management: an International Journal
Information Processing and Management: an International Journal
Evolutionary programming made faster
IEEE Transactions on Evolutionary Computation
Evolutionary programming using mutations based on the Levy probability distribution
IEEE Transactions on Evolutionary Computation
Multiobjective GAs, quantitative indices, and pattern classification
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
The problem of information overload in business organisations: a review of the literature
International Journal of Information Management: The Journal for Information Professionals
Hi-index | 12.05 |
With the explosive growth of web information, search engines have become the mainstream tools of information retrieval (IR). However, a notable problem emerged in the current IR systems is that the input queries are usually too short and too ambiguous to express their actual idea which largely affects the performance of IR systems. In this study, a novel query recommendation technology which suggests a list of related queries is proposed to resolve these problems. The query concepts can be firstly extracted from the web-snippets of the search result returned by the input query. A bipartite graph is subsequently built to identify the related queries, and the query similarity can be calculated by such bipartite graph. Moreover, by analyzing the URLs clicked by users, we find that some tokens appeared in URLs are very meaningful, especial for some typical topic-based pages. Therefore, these potential tokens which can provide a brief description from the subject of the URL are also considered. In order to reveal the real semantics between queries, the approach TF-IQF model is further discussed, and three features of a query, i.e. clicked documents, associated query and reversed query, are utilized in our approach in depth. Such a method could hopefully acquire the comprehensive idea of a query. To investigate how these three features could be used effectively for query recommendation in search engine, we adopt the benchmark evaluation criterions in our experiments, and the experimental results show its promising results in comparison with state of the art methods.