Learning to Rank Academic Experts in the DBLP Dataset

Expert finding is an information retrieval task that is concerned with the search for the most knowledgeable people with respect to a specific topic, and the search is based on documents that describe people's activities. The task involves taking a user query as input and returning a list of people who are sorted by their level of expertise with respect to the user query. Despite recent interest in the area, the current state-of-the-art techniques lack in principled approaches for optimally combining different sources of evidence. This article proposes two frameworks for combining multiple estimators of expertise. These estimators are derived from textual contents, from graph-structure of the citation patterns for the community of experts, and from profile information about the experts. More specifically, this article explores the use of supervised learning to rank methods, as well as rank aggregation approaches, for combing all of the estimators of expertise. Several supervised learning algorithms, which are representative of the pointwise, pairwise and listwise approaches, were tested, and various state-of-the-art data fusion techniques were also explored for the rank aggregation framework. Experiments that were performed on a dataset of academic publications from the Computer Science domain attest the adequacy of the proposed approaches.Comment: Expert Systems, 2013. arXiv admin note: text overlap with arXiv:1302.041

Ex-post assessment of merger effects: the case of Pfizer and Pharmacia (2003)

The paper studies the effects of the Pfizer and Pharmacia (2003) merger on competition in the Swiss pharmaceutical market and compares the assessment of the Swiss Competition Commission (COMCO) with the post-merger market developments. We find that the merger has had a miniscule impact on the Swiss pharmaceutical market. This has primarily to do with the fact that the product portfolios of both companies have shown no or only slight overlaps. In both cases of potential anticompetitive effects, the companies successfully proposed to divest some of their assets in order to prevent a further strengthening of their dominant position. The remedies included products in the development phase which were not available on the market at the time of the decision. In other markets in which either an overlapping of businesses of both companies existed or in which one of the merging entities held a dominant market position, no significant effects of the merger were noticed. This might have to do with both, existing price regulation in the Swiss drug industry and changes in Pfizer's product portfolio following the merger. Furthermore, with respect to other potentially interesting market characteristics such as investment behaviour, R&D, sales or employment, available data on global company level does not allow an isolation of the possible effects of the merger. --mergers,ex-post evaluation,pharmaceutical markets

Relative Importance of Environmental Attributes Using Logistic Regression

We investigate the problem of determining the relative importance of attributes in the discrete choice setting. Four alternative methods of extracting the relative importance of attributes are considered. The empirical application involves the development of a risk index system for individual herbicides combining the information on the herbicides' different human and environmental risks. The values of the pesticide risk indices are found to be consistent across the different methods.Environmental Economics and Policy,

Combining relevance information in a synchronous collaborative information retrieval environment

Traditionally information retrieval (IR) research has focussed on a single user interaction modality, where a user searches to satisfy an information need. Recent advances in both web technologies, such as the sociable web of Web 2.0, and computer hardware, such as tabletop interface devices, have enabled multiple users to collaborate on many computer-related tasks. Due to these advances there is an increasing need to support two or more users searching together at the same time, in order to satisfy a shared information need, which we refer to as Synchronous Collaborative Information Retrieval. Synchronous Collaborative Information Retrieval (SCIR) represents a significant paradigmatic shift from traditional IR systems. In order to support an effective SCIR search, new techniques are required to coordinate users' activities. In this chapter we explore the effectiveness of a sharing of knowledge policy on a collaborating group. Sharing of knowledge refers to the process of passing relevance information across users, if one user finds items of relevance to the search task then the group should benefit in the form of improved ranked lists returned to each searcher. In order to evaluate the proposed techniques we simulate two users searching together through an incremental feedback system. The simulation assumes that users decide on an initial query with which to begin the collaborative search and proceed through the search by providing relevance judgments to the system and receiving a new ranked list. In order to populate these simulations we extract data from the interaction logs of various experimental IR systems from previous Text REtrieval Conference (TREC) workshops

Single aggressive interactions increase urinary glucocorticoid levels in wild male chimpanzees

Financial support was provided by British Academy [http://www.britac.ac.uk/] (CC), Leakey Foundation [http://www.leakeyfoundation.org/] (CC, RMW, TD), Leverhulm Trust [http://www.leverhulme.ac.uk/] (KZ), Max Planck Society [http://www.eva.mpg.de/] (AW, CC, RMW, TD) and the Royal Zoological Society of Scotland [http://www.rzss.org.uk/], in providing core funding for Budongo Conservation Field Station. This project has received additional funding from the European Union’s Seventh Framework Program for research, technological development and demonstration [http://ec.europa.eu/research/fp7/index_e​n.cfm] under grant agreement no 283871.A basic premise in behavioural ecology is the cost-benefit arithmetic, which determines both behavioural decisions and evolutionary processes. Aggressive interactions can be costly on an energetic level, demanding increased energy or causing injuries, and on a psychological level, in the form of increased anxiety and damaged relationships between opponents. Here we used urinary glucocorticoid (uGC) levels to assess the costs of aggression in wild chimpanzees of Budongo Forest, Uganda. We collected 169 urine samples from nine adult male chimpanzees following 14 aggressive interactions (test condition) and 10 resting events (control condition). Subjects showed significantly higher uGC levels after single aggressive interactions compared to control conditions, likely for aggressors as well as victims. Higher ranking males had greater increases of uGC levels after aggression than lower ranking males. In contrast, uGC levels showed no significant change in relation to aggression length or intensity, indicating that psychological factors might have played a larger role than mere energetic expenditure. We concluded that aggressive behaviour is costly for both aggressors and victims and that costs seem poorly explained by energetic demands of the interaction. Our findings are relevant for studies of post-conflict interactions, since we provide evidence that both aggressors and victims experience a stress response to conflict.Publisher PDFPeer reviewe

Combining Household Income and Expenditure Data in Policy Simulations

Analysis of the distributional impact of fiscal policy proposals often requires information on household expenditures and incomes. It is unusual to have one data source with high quality information on both, and this problem is generally overcome with statistical matching of independent data sources. In this paper Grade Correspondence Analysis (GCA) is investigated as a tool to improve the matching process. An evaluation of alternative methods is conducted using datasets from the UK Family Expenditure Survey (FES), which is unusual in containing both income and expenditure at a detailed level of disaggregation. Imputed expenditures are compared with actual expenditures through the use of indirect tax simulations using the UK microsimulation model, POLIMOD. The most successful methods are then employed to enhance income data from the Family Resources Survey (FRS) and the synthetic dataset is used as a microsimulation model dataset