Construction of query concepts based on feature clustering of documents

In Information Retrieval, since it is hard to identify users’ information needs, many approaches have been tried to solve this problem by expanding initial queries and reweighting the terms in the expanded queries using users’ relevance judgments. Although relevance feedback is most effective when relevance information about retrieved documents is provided by users, it is not always available. Another solution is to use correlated terms for query expansion. The main problem with this approach is how to construct the term-term correlations that can be used effectively to improve retrieval performance. In this study, we try to construct query concepts that denote users’ information needs from a document space, rather than to reformulate initial queries using the term correlations and/or users’ relevance feedback. To form query concepts, we extract features from each document, and then cluster the features into primitive concepts that are then used to form query concepts. Experiments are performed on the Associated Press (AP) dataset taken from the TREC collection. The experimental evaluation shows that our proposed framework called QCM (Query Concept Method) outperforms baseline probabilistic retrieval model on TREC retrieval.     

The Dynamics of Opinion Formation in Local Popular Referendums: Why the Dutch Always Say No

There is growing research on voting behavior in referendums.However, the dynamics of opinion formation in popular referendums,referendums initiated by the electorate to approve or rejectdecisions made by representative bodies, has not yet been studied.This is especially unfortunate as voting decisions in popularreferendums differ from those in other referendums in interestingways. Opinion formation can be a very dynamic process in popularreferendums, making the referendum campaign crucial. This paperstudies the dynamics of opinion formation in popular referendumsand relates them to particular characteristics of the campaignsand the issues at hand. Based on the literature, we consideredthe effects of the intensity of the yes and no campaigns, familiaritywith the issue, and partisan cues. Our study uses content analysisdata and data from public opinion surveys dealing with variouspopular referendums held in the Netherlands. The study revealedseveral factors that contributed to the volatility of opinionsin the referendum campaigns: the issue (new and did not fittraditional political schemes), lack of support from societaland community organizations for the position of the local authorities,and low profile campaigns on the part of local authorities.While some of these factors are general and may play a rolein referendums everywhere, some can be considered ‘typicallyDutch’, related to the characteristics of popular referendumsin the Netherlands and the country’s political system.     

Russian Science Citation Index: Areas for Development Identified by Active Users

The current state of the Russian Science Citation Index is analyzed. Several areas for its further development identified by long-standing active users, such as data searching, refinement, and storage; current user alerts; data input with the Science Index license; patent information; and the application programming interface (API) are investigated.     

On the training of highly qualified scientific staff in the field of information security

This article considers the dynamics and specifics of training highly qualified scientific staff (philosophy doctors and doctors of sciences) in the field of information security and data protection in a 10-year period of 2004–2013 in basic research specialties as classified by the Higher Attestation Commission (VAC) of the Ministry of Education and Science of the Russian Federation.     

Neuroanatomy Learning: Augmented Reality vs. Cross-Sections

Neuroanatomy education is a challenging field which could benefit from modern innovations, such as augmented reality (AR) applications. This study investigates the differences on test scores, cognitive load, and motivation after neuroanatomy learning using AR applications or using cross-sections of the brain. Prior to two practical assignments, a pretest (extended matching questions, double-choice questions and a test on cross-sectional anatomy) and a mental rotation test (MRT) were completed. Sex and MRT scores were used to stratify students over the two groups. The two practical assignments were designed to study (1) general brain anatomy and (2) subcortical structures. Subsequently, participants completed a posttest similar to the pretest and a motivational questionnaire. Finally, a focus group interview was conducted to appraise participants’ perceptions. Medical and biomedical students (n = 31); 19 males (61.3%) and 12 females (38.7%), mean age 19.2 ± 1.7 years participated in this experiment. Students who worked with cross-sections (n = 16) showed significantly more improvement on test scores than students who worked with GreyMapp-AR (P = 0.035) (n = 15). Further analysis showed that this difference was primarily caused by significant improvement on the cross-sectional questions. Students in the cross-section group, moreover, experienced a significantly higher germane (P = 0.009) and extraneous cognitive load (P = 0.016) than students in the GreyMapp-AR group. No significant differences were found in motivational scores. To conclude, this study suggests that AR applications can play a role in future anatomy education as an add-on educational tool, especially in learning three-dimensional relations of anatomical structures.