Analysis of Statistical Question Classification for Fact-Based Questions

Question classification systems play an important role in question answering systems and can be used in a wide range of other domains. The goal of question classification is to accurately assign labels to questions based on expected answer type. Most approaches in the past have relied on matching questions against hand-crafted rules. However, rules require laborious effort to create and often suffer from being too specific. Statistical question classification methods overcome these issues by employing machine learning techniques. We empirically show that a statistical approach is robust and achieves good performance on three diverse data sets with little or no hand tuning. Furthermore, we examine the role different syntactic and semantic features have on performance. We find that semantic features tend to increase performance more than purely syntactic features. Finally, we analyze common causes of misclassification error and provide insight into ways they may be overcome.     

Online journals' impact on the citation patterns of medical faculty.

PURPOSE: The purpose was to determine the impact of online journals on the citation patterns of medical faculty. This study looked at whether researchers were more likely to limit the resources they consulted and cited to those journals available online rather than those only in print. SETTING: Faculty publications from the college of medicine at a large urban university were examined for this study. The faculty publications from a regional medical college of the same university were also examined in the study. The number of online journals available for faculty, staff, and students at this institution has increased from an initial core of 15 online journals in 1998 to over 11,000 online journals in 2004. METHODOLOGY: Searches by author affiliation were performed in the Web of Science to find all articles written by faculty members in the college of medicine at the selected institution. Searches were conducted for the following years: 1993, 1996, 1999, and 2002. Cited references from each faculty-authored article were recorded, and the corresponding cited journals were coded into four categories based on their availability at the institution in this study: print only, print and online, online only, and not owned. Results were analyzed using SPSS. RESULTS: The number of journals cited per year continued to increase from 1993 to 2002. The results did not indicate that researchers were more likely to cite online journals or were less likely to cite journals only in print. At the regional location where the number of print-only journals was minimal, use of the print-only journals did decrease in 2002, although not significantly. CONCLUSION/DISCUSSION: It is possible that electronic access to information (i.e., online databases) has had a positive impact on the number of articles faculty will cite. Results of this study suggest, at this point, that faculty are still accessing the print-only collection, at least for research purposes, and are therefore not sacrificing quality for convenience.     

Automated Classification to Improve the Efficiency of Weeding Library Collections

Previous studies have shown that weeding a library collection benefits patrons and increases circulation rates. However, the time required to review the collection and make weeding decisions presents a formidable obstacle. This study empirically evaluated methods for automatically classifying weeding candidates. A data set containing 80,346 items from a large-scale weeding project running from 2011 to 2014 at Wesleyan University was used to train six machine learning classifiers to predict a weeding decision of either ‘Keep’ or ‘Weed’ for each candidate. The study found statistically significant agreement (p?=?0.001) between classifier predictions and librarian judgments for all classifier types. The naive Bayes and linear support vector machine classifiers had the highest recall (fraction of items weeded by librarians that were identified by the algorithm), while the k-nearest-neighbor classifier had the highest precision (fraction of recommended candidates that librarians had chosen to weed). The variables found to be most relevant were: librarian and faculty votes for retention, item age, and the presence of copies in other libraries.     

Mandatory Student Fees and the Academic Library

As academic libraries' budgets remain flat while their expenditures rise, library leaders must seek out alternative sources of funding. One option is a mandatory student fee dedicated to the library. This article presents the results of a survey of 152 deans and directors of public R1 and R2 research universities that were asked whether their libraries benefit from mandatory student fees. While a library-specific fee is unusual, nearly half of responding libraries are eligible to receive some portion of another mandatory student fee. Study results can serve as evidence for libraries preparing to make a case for the significant, positive impact possible through even a modest library fee.     

Some Aspects of the Development of the All-Russian Institute for Scientific and Technical Information

Although the USSR and the United States had a comparable number of employees in the field of scientific information, there was a substantial difference in funding, which resulted in a lack of information support for Soviet scientists. While 90% of the publications in the United States were available almost immediately after their release, in the USSR they were delayed by 1.5 to 2 years. Since the publication of the Abstracts Journal by VINITI (AJ), its content was consistently expanding and reached its peak in 1990 (1.5 million documents per year). The next quarter of a century was characterized by a decline in both the composition of the AJ and the time required for its document coverage. The steps for restructuring VINITI activities are discussed. The focus is made on improving the limited coverage of the Russian-language part of the global flow of scientific information by Western information systems.     

Scientometric Instruments of Research Funding

The issues related to funding of public research organizations are explored. The history of scientometric information systems is outlined. The advantages and disadvantages of a bibliometric approach to financing of research organizations are analyzed. The link between the assessment of the scientific and technological potential of an institution and the optimal allocation of funds is investigated. Recommendations on how to improve the efficiency of public resources allocated for scientific research are presented.     

An Analytical Review of Global Ecoinformatics Problems

Modern global eco-dynamics problems are discussed. It is noted that global changes are mostly characterized by several key features, such as their multicomponent nature, as well as interactivity and nonlinearity. These features challenge various forecast estimates in such a way that the concept of forecasting has been replaced over the last few years by a much more ambiguous concept of scenarios. The vagueness of scenarios is due to the problem of global climate change. A global climate–nature–society system model is outlined.     

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.