Modeling information sources as integrals for effective and efficient source selection

In this paper, a new source selection algorithm for uncooperative distributed information retrieval environments is presented. The algorithm functions by modeling each information source as an integral, using the relevance score and the intra-collection position of its sampled documents in reference to a centralized sample index and selects the collections that cover the largest area in the rank-relevance space. Based on the above novel metric, the algorithm explicitly focuses on addressing the two goals of source selection; high-recall, which is important for source recommendation applications and high-precision which is important for distributed information retrieval, aiming to produce a high-precision final merged list.     

Narratives in Political Advertising: An Analysis of the Political Advertisements in the 2014 Midterm Elections

This study examined the use of narrative political advertisements during the 2014 midterm elections. A content analysis of 243 ads identified three narratives types: autobiographical, voter stories, and testimonials. Narrative ads were mostly positive and focused almost equally on issues and candidates’ characters. Negative attack ads and anonymous announcers were primarily used by candidates who lost the election, whereas winners employed more often autobiographical spots and included family members in the ads. The growing use of narratives in political advertising as found in the present study suggests that future research should further examine the effects of narrative political ads on individuals.     

A Virtual Learning Environment for the French Physics Teachers

This paper presents a study about the new roles that some French physics teachers develop in class when they use ICT. The presence of ICT in class practice seems to affect both the role of the teachers and how they teach. The content analysis of exchanged e-mails in two mailing lists and semi-structured interviews gives a glimpse on the way teachers are considering that their role in class is changing. New models of teaching seem to be constructed by teachers who feel more active and more dynamic when using ICT to teach physics. Thanks to the introduction of the ICT they have become mediators for their students. Scientific knowledge is no longer on the teacher's side but it is now shared between different sources. They present also the use of ICT as a form of life long learning. Furthermore, the teachers consider that the mailing lists facilitate the communication and contribute to the progress of educational practices.     

A results merging algorithm for distributed information retrieval environments that combines regression methodologies with a selective download phase

The problem of results merging in distributed information retrieval environments has gained significant attention the last years. Two generic approaches have been introduced in research. The first approach aims at estimating the relevance of the documents returned from the remote collections through ad hoc methodologies (such as weighted score merging, regression etc.) while the other is based on downloading all the documents locally, completely or partially, in order to calculate their relevance. Both approaches have advantages and disadvantages. Download methodologies are more effective but they pose a significant overhead on the process in terms of time and bandwidth. Approaches that rely solely on estimation on the other hand, usually depend on document relevance scores being reported by the remote collections in order to achieve maximum performance. In addition to that, regression algorithms, which have proved to be more effective than weighted scores merging algorithms, need a significant number of overlap documents in order to function effectively, practically requiring multiple interactions with the remote collections. The new algorithm that is introduced is based on adaptively downloading a limited, selected number of documents from the remote collections and estimating the relevance of the rest through regression methodologies. Thus it reconciles the above two approaches, combining their strengths, while minimizing their drawbacks, achieving the limited time and bandwidth overhead of the estimation approaches and the increased effectiveness of the download. The proposed algorithm is tested in a variety of settings and its performance is found to be significantly better than the former, while approximating that of the latter.