Map integrity constraint verification by using visual language parsing - Fatto, V.D.; Deufemia, V.; Paolino, L. (Journal of Digital Information Management, 2008)
In the last decade there has been an increasing interest in the use of tools for the creation of geographic maps. However, these tools include functionalities that allow users to insert information without verifying their consistency with the constraints defined by the designer. In this paper we propose an approach based on visual language parsing for guaranteeing the integrity of data produced during the map editing process. According to our approach, constraints are expressed by using high-level data model, such as OMT-G, and converted in a proper visual language grammar automatically. From such a grammar, a parser able to identify incorrect aggregation of spatial data input is generated. The grammar formalism also allows us to associate suitable semantic actions with productions in order to perform automatic corrections of inconsistent input data, error recognition and visualization, prompting actions for error recovery. We also present a system prototype supporting the proposed process.
Keywords: Data Quality; Grammar Formalism; Integrity Constraint Checking; Spatial Consistency; Topological Relationships; Visual Language Parsing

Personalized document ranking: Exploiting evidence from multiple user interests for profiling and retrieval - Tamine-Lechani, L.; Boughanem, M.; Zemirli, N. (Journal of Digital Information Management, 2008)
The goal of personalization in information retrieval is to tailor the search engine results to the specific goals, preferences and general interests of the users. We propose a novel model for both user profiling and document ranking that consider the user interests as sources of evidence in order to tune the accuracy of the documents returned in response to the user query. User profiling is performed by managing the user search history using statistical based operators in order to highlight the user short-term interests seen as surrogates for building the long-term ones. The document ranking model's foundation comes from influence diagrams which are extension of Bayesian graphs, dedicated to decision-making problems. Hence, query evaluation is carried out as an inference process that aims at computing an aggregated utility of a document by considering its relevance to the query but also the corresponding utility with regard to the user's topics of interest. Experimental results using enhanced TREC collections indicate that our personalized retrieval model is effective.
Cited By (since 1996):14Export Date: 10 July 2014
Keywords: Data Quality; Grammar Formalism; Integrity Constraint Checking; Spatial Consistency; Topological Relationships; Visual Language Parsing