Possibilistic networks for information retrieval

Query Propagation in Possibilistic Information Retrieval Networks

This paper proposes a new Information Retrieval Model based on possibility and necessity measures. This model encodes relationship dependencies existing between terms, documents and query by possibilistic networks. The user’s query triggers a propagation process to retrieve necessarily or at least possibly relevant documents.

A Model for Information Retrieval Based on Possibilistic Networks

This paper proposes a model for Information Retrieval (IR) based on possibilistic directed networks. Relations documents-terms and query-terms are modeled through possibility and necessity measures rather than a probability measure. The relevance value for the document given the query is measured by two degrees: the necessity and the possibility. More precisely, the user’s query triggers a prop...

Information Retrieval by Possibilistic Reasoning

Public Transport Ontology for Passenger Information Retrieval

Passenger information aims at improving the user-friendliness of public transport systems while influencing passenger route choices to satisfy transit user’s travel requirements. The integration of transit information from multiple agencies is a major challenge in implementation of multi-modal passenger information systems. The problem of information sharing is further compounded by the multi-l...

Possibilistic Model for Relevance Feedback in Collaborative Information Retrieval

Web information is too heterogeneous that users have difficulties to retrieve their needed information: text, image orvideo. In this context, the collaborative work presents one solution proposed to solve this problem. Collaborative retrieval enables the retrieval histories’ sharing between users having the same profile across multiple tools such as annotations. We propose in this paper to impr...