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

DCU at MediaEval 2010 – Tagging task WildWildWeb

We describe our runs and results for the fixed label Wild Wild Web Tagging Task at MediaEval 2010. Our experiments indicate that including all words in the ASR transcripts of the document set results in better labeling accuracy than restricting the index to only words with recognition confidence above a fixed level. Additionally our results show that tagging accuracy can be improved by incorporating additional metadata describing the documents where it is available

Achieving Secure and Efficient Cloud Search Services: Cross-Lingual Multi-Keyword Rank Search over Encrypted Cloud Data

Multi-user multi-keyword ranked search scheme in arbitrary language is a novel multi-keyword rank searchable encryption (MRSE) framework based on Paillier Cryptosystem with Threshold Decryption (PCTD). Compared to previous MRSE schemes constructed based on the k-nearest neighbor searcha-ble encryption (KNN-SE) algorithm, it can mitigate some draw-backs and achieve better performance in terms of functionality and efficiency. Additionally, it does not require a predefined keyword set and support keywords in arbitrary languages. However, due to the pattern of exact matching of keywords in the new MRSE scheme, multilingual search is limited to each language and cannot be searched across languages. In this pa-per, we propose a cross-lingual multi-keyword rank search (CLRSE) scheme which eliminates the barrier of languages and achieves semantic extension with using the Open Multilingual Wordnet. Our CLRSE scheme also realizes intelligent and per-sonalized search through flexible keyword and language prefer-ence settings. We evaluate the performance of our scheme in terms of security, functionality, precision and efficiency, via extensive experiments

Simple sequence repeats in zebra finch (Taeniopygia guttata) expressed sequence tags: a new resource for evolutionary genetic studies of passerines

Background Passerines (perching birds) are widely studied across many biological disciplines including ecology, population biology, neurobiology, behavioural ecology and evolutionary biology. However, understanding the molecular basis of relevant traits is hampered by the paucity of passerine genomics tools. Efforts to address this problem are underway, and the zebra finch (Taeniopygia guttata) will be the first passerine to have its genome sequenced. Here we describe a bioinformatic analysis of zebra finch expressed sequence tag (EST) Genbank entries. Results A total of 48,862 ESTs were downloaded from GenBank and assembled into contigs, representing an estimated 17,404 unique sequences. The unique sequence set contained 638 simple sequence repeats (SSRs) or microsatellites of length ≥20 bp and purity ≥90% and 144 simple sequence repeats of length ≥30 bp. A chromosomal location for the majority of SSRs was predicted by BLASTing against assembly 2.1 of the chicken genome sequence. The relative exonic location (5' untranslated region, coding region or 3' untranslated region) was predicted for 218 of the SSRs, by BLAST search against the ENSEMBL chicken peptide database. Ten loci were examined for polymorphism in two zebra finch populations and two populations of a distantly related passerine, the house sparrow Passer domesticus. Linkage was confirmed for four loci that were predicted to reside on the passerine homologue of chicken chromosome 7. Conclusion We show that SSRs are abundant within zebra finch ESTs, and that their genomic location can be predicted from sequence similarity with the assembled chicken genome sequence. We demonstrate that a useful proportion of zebra finch EST-SSRs are likely to be polymorphic, and that they can be used to build a linkage map. Finally, we show that many zebra finch EST-SSRs are likely to be useful in evolutionary genetic studies of other passerines

The Transition to...Open Access

This report describes and draws conclusions from the transition of the Association for Learning Technology’s journal Research in Learning Technology from toll-access to Open Access, and from being published by one of the "big five" commercial publishers to being published by a specialist Open Access publisher. The focus of the report is on what happened in the run-up to and after the transition, rather than on the process of deciding to switch between publishing models, which is covered in in ALT's 2011 report "Journal tendering for societies: a brief guide" - http://repository.alt.ac.uk/887/

Blogs, wikis and creative innovation

blogs, internet, innovation

POIReviewQA: A Semantically Enriched POI Retrieval and Question Answering Dataset

Many services that perform information retrieval for Points of Interest (POI) utilize a Lucene-based setup with spatial filtering. While this type of system is easy to implement it does not make use of semantics but relies on direct word matches between a query and reviews leading to a loss in both precision and recall. To study the challenging task of semantically enriching POIs from unstructured data in order to support open-domain search and question answering (QA), we introduce a new dataset POIReviewQA. It consists of 20k questions (e.g."is this restaurant dog friendly?") for 1022 Yelp business types. For each question we sampled 10 reviews, and annotated each sentence in the reviews whether it answers the question and what the corresponding answer is. To test a system's ability to understand the text we adopt an information retrieval evaluation by ranking all the review sentences for a question based on the likelihood that they answer this question. We build a Lucene-based baseline model, which achieves 77.0% AUC and 48.8% MAP. A sentence embedding-based model achieves 79.2% AUC and 41.8% MAP, indicating that the dataset presents a challenging problem for future research by the GIR community. The result technology can help exploit the thematic content of web documents and social media for characterisation of locations