Talk by Prof. Norbert Fuhr on "Negation, Contradiction and Credibility in Information Retrieval"
Channel: IIIA Hub
Date: 2021-10-05

Title:

Negation, Contradiction and Credibility in Information Retrieval

Abstract:

For searching for negative information (like e.g. 'muesli, no sugar' or 'mobile phone, no contract') no satisfying solutions have been provided so far. Although there is a NOT operator in many systems, it actually searches for the absence of terms, not their negation. Logically, this behavior corresponds to the closed world assumption, which is well-known in the database field. In IR, however, we are dealing with uncertain and incomplete knowledge; thus, an open world assumption would be more appropriate. 
A related problem is the aggregation of different statements, e.g. from user reviews of services or products. When modeling negative statements explicitly, we also have to handle contradictions. Furthermore, reviews may differ in their credibility. For addressing these issues, we present an approach based on probabilistic four-valued logic, and show experimental results for its application to hotel reviews.

Bio:

Norbert Fuhr holds a PhD (Dr.) in Computer Science from the Technical University of Darmstadt, which he received in 1986. He became Associate Professor in the computer science department of the University of Dortmund in 1991 and was appointed Full Professor for computer science at the University of Duisburg-Essen in 2002. 
His past research dealt with topics such as probabilistic retrieval models, the integration of IR and databases, retrieval in distributed digital libraries and XML documents, and user friendly retrieval interfaces. His current research interests are models for interactive retrieval, domain-specific IR methods and IR evaluation methodology
Norbert Fuhr has served as PC member and program chair of major conferences in IR and digital libraries, and on the editorial boards of several journals in these areas.
In 2012, Norbert Fuhr received the Gerald Salton Award of ACM-SIGIR.