Semantic Categorization Of Online Video

As internet users are increasing day by day, the users of video-sharing site are also increasing. Video-sharing is becoming more and more popular in e-learing, but the current famous websites like youtube are not structured when it come to serving the purpose of providing educational videos for preschool and high school students. There is a need to fill building more educationally focused video site, where the content is more structured, easy to use, support both direct search and browsing, and follow a particular curriculum for preschool and high school students. This report discuss the issues like categorization and search interface of these sites and propose alternatives to existing ones out there. In this project, I have built an educational website for preschool, high school, and college level students concentrating on improved categorization and search interface of the site. This report provides detail description of my system and the results of comparison between my site and youtube. supraj

Slicing and dicing the information space using local contexts

In recent years there has been growing interest in faceted grouping of documents for Interactive Information Retrieval (IIR). It is suggested that faceted grouping can offer a flexible way of browsing a collection compared to clustering. However, the success of faceted grouping seems to rely on sufficient knowledge of collection structure. In this paper we propose an approach based on the local contexts of query terms, which is inspired by the interaction of faceted search and browsing. The use of local contexts is appealing since it requires less knowledge of the collection than existing approaches. A task-based user study was carried out to investigate the effectiveness of our interface in varied complexity. The results suggest that the local contexts can be exploited as the source of search result browsing in IIR, and that our interface appears to facilitate different aspects of search process over the task complexity. The implication of the evaluation methodology using high complexity tasks is also discussed

You can't always sketch what you want: Understanding Sensemaking in Visual Query Systems

Visual query systems (VQSs) empower users to interactively search for line charts with desired visual patterns, typically specified using intuitive sketch-based interfaces. Despite decades of past work on VQSs, these efforts have not translated to adoption in practice, possibly because VQSs are largely evaluated in unrealistic lab-based settings. To remedy this gap in adoption, we collaborated with experts from three diverse domains---astronomy, genetics, and material science---via a year-long user-centered design process to develop a VQS that supports their workflow and analytical needs, and evaluate how VQSs can be used in practice. Our study results reveal that ad-hoc sketch-only querying is not as commonly used as prior work suggests, since analysts are often unable to precisely express their patterns of interest. In addition, we characterize three essential sensemaking processes supported by our enhanced VQS. We discover that participants employ all three processes, but in different proportions, depending on the analytical needs in each domain. Our findings suggest that all three sensemaking processes must be integrated in order to make future VQSs useful for a wide range of analytical inquiries.Comment: Accepted for presentation at IEEE VAST 2019, to be held October 20-25 in Vancouver, Canada. Paper will also be published in a special issue of IEEE Transactions on Visualization and Computer Graphics (TVCG) IEEE VIS (InfoVis/VAST/SciVis) 2019 ACM 2012 CCS - Human-centered computing, Visualization, Visualization design and evaluation method

Multiple-taxonomy question classification for category search on faceted information

In this paper we present a novel multiple-taxonomy question classification system, facing the challenge of assigning categories in multiple taxonomies to natural language questions. We applied our system to category search on faceted information. The system provides a natural language interface to faceted information, detecting the categories requested by the user and narrowing down the document search space to those documents pertaining to the facet values identified. The system was developed in the framework of language modeling, and the models to detect categories are inferred directly from the corpus of documents.This work has been partially supported by the framework of the project QALL-ME (FP6-IST-033860), which is a 6th Framenwork Research Programme of the European Union (EU), and the Spanish Government, project TEXT-MESS (TIN-2006-15265- C06-01)

Resources Annotation, Retrieval and Presentation: a semantic annotation management system

International audienceThis paper addresses the problem of the management of resources metadata. A variety of responses are discussed, and we describe one possible way forward, which uses a semantic annotation management tool. The term 'semantic' describes the ability to create, retrieve, query and navigate knowledgeably about things identified by a Web URI. The support for this semantic tool is RDF, through the integration of Jena, an open-source RDF API provided by HP laboratory. Thanks to RDF capabilities, this tool offers new search features such as hierarchical browsing based on the structure of RDF vocabularies and faceted-browsing using properties lists defined by the end-user. The navigation inside annotations uses intuitive modes such as left/right and backward/forward movements. Presentation is controlled by the user using a subset of the Fresnel language to specify how RDF graphs are presented. This work is ongoing; certain open issues are raised