Combining Text and Formula Queries in Math Information Retrieval: Evaluation of Query Results Merging Strategies

Specific to Math Information Retrieval is combining text with mathematical formulae both in documents and in queries. Rigorous evaluation of query expansion and merging strategies combining math and standard textual keyword terms in a query are given. It is shown that techniques similar to those known from textual query processing may be applied in math information retrieval as well, and lead to a cutting edge performance. Striping and merging partial results from subqueries is one technique that improves results measured by information retrieval evaluation metrics like Bpref

Use of implicit graph for recommending relevant videos: a simulated evaluation

In this paper, we propose a model for exploiting community based usage information for video retrieval. Implicit usage information from a pool of past users could be a valuable source to address the difficulties caused due to the semantic gap problem. We propose a graph-based implicit feedback model in which all the usage information can be represented. A number of recommendation algorithms were suggested and experimented. A simulated user evaluation is conducted on the TREC VID collection and the results are presented. Analyzing the results we found some common characteristics on the best performing algorithms, which could indicate the best way of exploiting this type of usage information

Unsupervised, Efficient and Semantic Expertise Retrieval

We introduce an unsupervised discriminative model for the task of retrieving experts in online document collections. We exclusively employ textual evidence and avoid explicit feature engineering by learning distributed word representations in an unsupervised way. We compare our model to state-of-the-art unsupervised statistical vector space and probabilistic generative approaches. Our proposed log-linear model achieves the retrieval performance levels of state-of-the-art document-centric methods with the low inference cost of so-called profile-centric approaches. It yields a statistically significant improved ranking over vector space and generative models in most cases, matching the performance of supervised methods on various benchmarks. That is, by using solely text we can do as well as methods that work with external evidence and/or relevance feedback. A contrastive analysis of rankings produced by discriminative and generative approaches shows that they have complementary strengths due to the ability of the unsupervised discriminative model to perform semantic matching.Comment: WWW2016, Proceedings of the 25th International Conference on World Wide Web. 201

Towards the semantic interpretation of personal health messages from social media

Recent attempts have been made to utilise social media platforms, such as Twitter, to provide early warning and monitoring of health threats in populations (i.e. Internet biosurveillance). It has been shown in the literature that a system based on keyword matching that exploits social media messages could report flu surveillance well ahead of the Centers of Disease Control and Prevention (CDC). However, we argue that a simple keyword matching may not capture semantic interpretation of social media messages that would enable healthcare experts or machines to extract and leverage medical knowledge from social media messages. In this paper, we motivate and describe a new task that aims to tackle this technology gap by extracting semantic interpretation of medical terms mentioned in social media messages, which are typically written in layman’s language. Achieving such a task would enable an automatic integration between the data about direct patient experiences extracted from social media and existing knowledge from clinical databases, which leads to advances in the use of community health experiences in healthcare services.The authors gratefully acknowledge funding from the EPSRC (grant number EP/M005089/1)This is the author accepted manuscript. The final version is available from ACM via http://dx.doi.org/10.1145/2811271.281127

Investigation of MoOx/Al2O3 under cyclic operation for oxidative and non-oxidative dehydrogenation of propane

A MoOx/Al2O3 catalyst was synthesised and tested for oxidative (ODP) and non-oxidative (DP) dehydrogenation of propane in a reaction cycle of ODP followed by DP and a second ODP run. Characterisation results show that the fresh catalyst contains highly dispersed Mo oxide species in the +6 oxidation state with tetrahedral coordination as [MoVIO4]2− moieties. In situ X-ray Absorption Spectroscopy (XAS) shows that [MoVIO4]2− is present during the first ODP run of the reaction cycle and is reduced to MoIVO2 in the following DP run. The reduced species are partly re-oxidised in the subsequent second ODP run of the reaction cycle. The partly re-oxidised species exhibit oxidation and coordination states that are lower than 6 but higher than 4 and are referred to as MoxOy. These species significantly improved propene formation (relatively 27% higher) in the second ODP run at similar propane conversion activity. Accordingly, the initial tetrahedral [MoVIO4]2− present during the first ODP run of the reaction cycle is active for propane conversion; however, it is unselective for propene. The reduced MoIVO2 species are relatively less active and selective for DP. It is suggested that the MoxOy species generated by the reaction cycle are active and selective for ODP. The vibrational spectroscopic data indicate that the retained surface species are amorphous carbon deposits with a higher proportion of aromatic/olefinic like species

The Complex Dynamics of Sponsored Search Markets

This paper provides a comprehensive study of the structure and dynamics of online advertising markets, mostly based on techniques from the emergent discipline of complex systems analysis. First, we look at how the display rank of a URL link influences its click frequency, for both sponsored search and organic search. Second, we study the market structure that emerges from these queries, especially the market share distribution of different advertisers. We show that the sponsored search market is highly concentrated, with less than 5% of all advertisers receiving over 2/3 of the clicks in the market. Furthermore, we show that both the number of ad impressions and the number of clicks follow power law distributions of approximately the same coefficient. However, we find this result does not hold when studying the same distribution of clicks per rank position, which shows considerable variance, most likely due to the way advertisers divide their budget on different keywords. Finally, we turn our attention to how such sponsored search data could be used to provide decision support tools for bidding for combinations of keywords. We provide a method to visualize keywords of interest in graphical form, as well as a method to partition these graphs to obtain desirable subsets of search terms

Financial Characteristics of Companies Audited by Large Audit Firms

Purpose “ The purpose of this paper is to examine how financial characteristics associated with the choice of a big audit firm with further investigation on the agency costs of free cash flows.Design/methodology/approach “ The sample used for this work includes industrial listed companies from Germany and France. To test our hypothesis, we used a number of logit models, extending the standard model selection audit firm, to include the variables of interest. Following previous work, our dependent dummy variable is Big4 or non-Big4.Findings “ We observed that most independent variables in the German companies show similar results to previous work, but we did not have the same results for the French industry. Moreover, our findings suggest that the total debt and dividends can be an important reason for determining the choice of a large audit firm, reducing agency costs of free cash flows.Research limitations/implications “ This study has some limitations on the measurements of the cost of the audit fees and also generates opportunities for additional searching.Originality/value “ The paper provides only one aspect to explain the relationship between the problems of agency costs of free cash flow and influence in choosing a large auditing firm, which stems from investors\u27 demand for higher quality audits