PUMA
Istituto di Scienza e Tecnologie dell'Informazione     
Broccolo D., Marcon L., Nardini F. M., Perego R., Silvestri F. Generating suggestions for queries in the long tail with an inverted index. In: Information Processing & Management, vol. 48 (2) pp. 326 - 339. Elsevier, 2012.
 
 
Abstract
(English)
This paper proposes an efficient and effective solution to the problem of choosing the queries to suggest to web search engine users in order to help them in rapidly satisfying their information needs. By exploiting a weak function for assessing the similarity between the current query and the knowledge base built from historical users' sessions, we re-conduct the suggestion generation phase to the processing of a full-text query over an inverted index. The resulting query recommendation technique is very efficient and scalable, and is less affected by the data-sparsity problem than most state-of-the-art proposals. Thus, it is particularly effective in generating suggestions for rare queries occurring in the long tail of the query popularity distribution. The quality of suggestions generated is assessed by evaluating the effectiveness in forecasting the users' behavior recorded in historical query logs, and on the basis of the results of a reproducible user study conducted on publicly-available, human-assessed data. The experimental evaluation conducted shows that our proposal remarkably outperforms two other state-of-the-art solutions, and that it can generate useful suggestions even for rare and never seen queries.
URL: http://www.sciencedirect.com/science/article/pii/S0306457311000756
DOI: 10.1016/j.ipm.2011.07.005
Subject Query recommender systems
Efficiency in query suggestion
Data sparsity problem
Effectiveness evaluation metrics
H.2.8 Database Applications. Data Mining
H.3.3 Information Search and Retrieval. Search process
H.3.3 Information Search and Retrieval. Query formulation


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