An empirical study of inter-concept similarities in multimedia ontologies

Generic concept detection has been a widely studied topic in recent research on multimedia analysis and retrieval, but the issue of how to exploit the structure of a multimedia ontology as well as different inter-concept relations, has not received similar attention. In this paper, we present results from our empirical analysis of different types of similarity among semantic concepts in two multimedia ontologies, LSCOM-Lite and CDVP-206. The results show promise that the proposed methods may be helpful in providing insight into the existing inter-concept relations within an ontology and selecting the most facilitating set of concepts and hierarchical relations. Such an analysis as this can be utilized in various tasks such as building more reliable concept detectors and designing large-scale ontologies

Semantic Search Using a Similarity Graph

Given a set of documents and an input query that is expressed in a natural language, the problem of document search is retrieving the most relevant documents. Unlike most existing systems that perform document search based on keywords matching, we propose a search method that considers the meaning of the words in the query and the document. As a result, our algorithm can return documents that have no words in common with the input query as long as the documents are relevant. For example, a document that contains the words “Ford”, “Chrysler” and “General Motors” multiple times is surely relevant for the query “car” even if the word “car” does not appear in the document. Our semantic search algorithm is based on a similarity graph that contains the degree of semantic similarity between terms, where a term can be a word or a phrase. We experimentally validate our algorithm on the Cranfield benchmark that contains 1400 documents and 225 natural language queries. The benchmark also contains the relevant documents for every query as determined by human judgment. We show that our semantic search algorithm produces a higher value for the mean average precision (MAP) score than a keywords matching algorithm. This shows that our approach can improve the quality of the result because the meaning of the words and phrases in the documents and the queries is taken into account

An architecture for mining resources complementary to audio-visual streams

In this paper we attempt to characterize resources of information complementary to audio-visual (A/V) streams and propose their usage for enriching A/V data with semantic concepts in order to bridge the gap between low-level video detectors and high-level analysis. Our aim is to extract cross-media feature descriptors from semantically enriched and aligned resources so as to detect finer-grained events in video.We introduce an architecture for complementary resource analysis and discuss domain dependency aspects of this approach related to our domain of soccer broadcasts

CONTEXT-BASED AUTOSUGGEST ON GRAPH DATA

Autosuggest is an important feature in any search applications. Currently, most applications only suggest a single term based on how frequent that term appears in the indexed documents or how often it is searched upon. These approaches might not provide the most relevant suggestions because users often enter a series of related query terms to answer a question they have in mind. In this project, we implemented the Smart Solr Suggester plugin using a context-based approach that takes into account the relationships among search keywords. In particular, we used the keywords that the user has chosen so far in the search text box as the context to autosuggest their next incomplete keyword. This context-based approach uses the relationships between entities in the graph data that the user is searching on and therefore would provide more meaningful suggestions

Creating a Phrase Similarity Graph From Wikipedia

The paper addresses the problem of modeling the relationship between phrases in English using a similarity graph. The mathematical model stores data about the strength of the relationship between phrases expressed as a decimal number. Both structured data from Wikipedia, such as that the Wikipedia page with title “Dog” belongs to theWikipedia category “Domesticated animals”, and textual descriptions, such as that the Wikipedia page with title “Dog” contains the word “wolf” thirty one times are used in creating the graph. The quality of the graph data is validated by comparing the similarity of pairs of phrases using our software that uses the graph with results of studies that were performed with human subjects. To the best of our knowledge, our software produces better correlation with the results of both the Miller and Charles study and the WordSimilarity-353 study than any other published research

The Production of Docility in Professional Ice Hockey

The social relations and practices that imbue the sport of ice hockey have prompted several limiting and problematic outcomes for athletes. Concerned by such outcomes, and informed by the anatomo-politics of French poststructuralist philosopher Michel Foucault (1991), an examination into the relations of power that govern North American professional ice hockey was undertaken. The examination revealed that athletes were routinely subject to disciplinary power and a commonplace set of practices that closely resemble Foucault’s (1991) ‘means of correct training’: managers, in partnership with coaches under their remit, choreographed and engaged in constant supervision (e.g., scouting and monitoring), organized highly ritualized examinations (e.g., combines, training camps), rewarded conformity (e.g., contractual benefits), and punished deviance (e.g., inter- and intra-team reassignments). These practices were additionally undergirded by clearly identifiable panoptic arrangements that stretched across the athletic lifespan. Ultimately, the observed workings of disciplinary power served not the development of a whole individual, but rather the production of docility

Exploring Perceptions of Group Processes in Ice Hockey Officiating

This is an Original Manuscript of an article published by Taylor & Francis in Journal of Applied Sport Psychology on 10 July 2017, available online: http://www.tandfonline.com/10.1080/10413200.2017.1349208.Understanding factors that influence sport officials’ performance is vital to ensuring fair sport competition. Through semi-structured interviews (N = 17), we explored officials’ perceptions of group processes that occurred among ice hockey officiating teams. Participant responses revealed numerous ways that group processes were present within officials’ interactions, and two unique characteristics involved the transient nature of officiating groups (frequently performing with different officials) and intra-team competition pertaining to post-season assignments. In the discussion, we expand on the unique nature of officiating groups, synthesize activities in which officials seek to enhance groupness, and provide insights for future interventions and researchers