Lobna Hlaoua

XFIRM at INEX 2005: ad-hoc and relevance feedback tracks

This paper describes experiments carried out with the XFIRM system in the INEX 2005 framework. The XFIRM system uses a relevance propagation method to answer CO and CAS queries. Runs were submitted to the ad-hoc and relevance feedback tracks.

Combination of evidences in relevance feedback for xml retrieval

The main objective in XML Retrieval is to select the relevant elements of XML document instead of the whole document. Many open issues appear when considering Relevance Feedback (RF) in XML documents. They are mainly related to the form of XML documents, which mix content and structure information and to the new information granularity. In this paper, a new flexible method of relevance feedback in XML retrieval using two sources of evidence is described. We propose to use the context criterion to select terms to extend the initial query and to use generative structures to express structural constraints. Both approaches are applied in different combined forms. Experiments are carried out with the INEX evaluation campaign and results show the effectiveness of our approach.

Relevance feedback revisited: dealing with content and structure in XML documents

Relevance feedback (RF) is a technique that allows to enrich an initial query according to the user feedback. The goal is to express more precisely the user’s needs. Some open issues arise when considering semi-structured documents like XML documents. They are mainly related to the form of XML documents which mix content and structure information and to the new granularity of information. Indeed, the main objective of XML retrieval is to select relevant elements in XML documents instead of whole documents. Most of the RF approaches proposed in XML retrieval are simple adaptation of traditional RF to the new granularity of information. They usually enrich queries by adding terms extracted from relevant elements instead of terms extracted from whole documents. In this article, we describe a new approach of RF that takes advantage of two sources of evidence: the content and the structure. We propose to use the query term proximity to select terms to be added to the initial query and to use generic structures to express structural constraints. Both sources of evidence are used in different combined forms. Experiments were carried out within the INEX evaluation campaign and results show the effectiveness of our approaches.

XML retrieval: what about using contextual relevance?

The aim of this study is to evaluate the impact of context to better identify relevant elements in XML retrieval. Context is represented here by clues on whole document relevance. We represent context according to different points of view: by introducing document dimension while computing terms weights, by using document relevance when evaluating elements relevance or by ranking elements on document relevance. Experiments were undertaken on INEX collection, and results showed the interest of contextual relevance and a relative high precision of our proposal comparing to INEX official results.

XFIRM at INEX 2006. Ad-Hoc, Relevance Feedback and MultiMedia Tracks

This paper describes experiments carried out with the XFIRM system in the INEX 2006 framework. The XFIRM system uses a relevance propagation method to answer CO and CO+S queries. Runs were submitted to the ad-hoc, relevance feedback and multimedia tracks.

A structure-oriented relevance feedback method for XML retrieval

Relevance Feedback (RF) is a technique allowing to enrich an initial query according to the user feedback. The goal is to express more precisily the users needs. Some open issues appear when considering semi-structured documents like XML documents. Most of the RF approaches proposed in XML retrieval are simple adaptations of traditional RF to the new granularity of information. They enrich queries by adding terms extracted from relevant elements instead of terms extracted from whole documents. In this paper we show how structural constraints can also be used in RF. We propose a new approach that is able to extend the initial query by adding one or more generative structures. This approach is applied to unstructured queries. Experiments are carried out on INEX collection and results show the interest of our method.