DCU-TCD@LogCLEF 2010: Re-ranking Document Collections and Query Performance Estimation
GHORAB, MOHAMMED RAMI ELHUSSEIN
JONES, GARETH J. F.
WADE, VINCENT PATRICK
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Citation:Johannes Leveling, M. Rami Ghorab, Walid Magdy, Gareth J. F. Jones, Vincent Wade, DCU-TCD@LogCLEF 2010: Re-ranking Document Collections and Query Performance Estimation, 2010
Abstract. This paper describes the collaborative participation of Dublin City University and Trinity College Dublin in LogCLEF 2010. Two sets of experiments were conducted. First, different aspects of the TEL query logs were analysed after extracting user sessions of consecutive queries on a topic. The relation between the queries and their length (number of terms) and position (first query or further reformulations) was examined in a session with respect to query performance estimators such as query scope, IDF-based measures, simplified query clarity score, and average inverse document collection frequency. Results of this analysis suggest that only some estimator values show a correlation with query length or position in the TEL logs (e.g. similarity score between collection and query). Second, the relation between three attributes was investigated: the user's country (detected from IP address), the query language, and the interface language. The investigation aimed to explore the influence of the three attributes on the user's collection selection. Moreover, the investigation involved assigning different weights to the three attributes in a scoring function that was used to re-rank the collections displayed to the user according to the language and country. The results of the collection re-ranking show a significant improvement in Mean Average Precision (MAP) over the original collection ranking of TEL. The results also indicate that the query language and interface language have more in fluence than the user's country on the collections selected by the users.
Science Foundation Ireland
Query Performance Esitmation
Cross-Language Information Retrieval
Multilingual Information Retrieval