Let Google index your media fragments

Current multimedia applications in Web 2.0 have generated a massive amount of multimedia resources, but most search results for multimedia resources still focus on the whole re-source level. Media fragments expose the inside content of multimedia resources for annotations, but they are yet fully explored and indexed by major search engines. W3C has published Media Fragment 1.0 as a standard way to describe media fragments on the Web. In this proposal, we make use of Google's Ajax Application Crawler to index media fragments represented by Media Fragment URIs. Each media fragment with related annotations will have an individual snapshot page, which could be indexed by the crawler. Initial evaluation has shown that the snapshot pages are successfully fetched by Googlebot and we are expecting more media fragments to be indexed using this method, so that the search for multimedia resources would be more efficient

ChemINDEX Database; The Professional's Version of ChemFinder.Com

ChemFinder.Com and ChemINDEX are interfaces that access the same database. ChemINDEX, however, provides greatly enhanced search, display and customization features (and without any pop-up ads). The common database has indexed nearly 80K compounds (with an additional 160K synonyms) from over 800 publicly available sites

reSearch : enhancing information retrieval with images

Combining image and text search is an open research question. The main issues are what technologies to base this solution on, and what measures of relevance to employ. Our reSearch prototype mashes up papers indexed using information retrieval techniques (Terrier) with Google image search for faces and Google book search. The user can interactively employ query expansion with additional terms suggested by Terrier, and use those terms to expand both the text and image search. We test this solution with a selection of recent publications and queries concerning people engaged in research. We report on the effectiveness of this solution. It seems that the combination works to a large extent, as testified by our observations

Evolving Lucene search queries for text classification

We describe a method for generating accurate, compact, human understandable text classifiers. Text datasets are indexed using Apache Lucene and Genetic Programs are used to construct Lucene search queries. Genetic programs acquire fitness by producing queries that are effective binary classifiers for a particular category when evaluated against a set of training documents. We describe a set of functions and terminals and provide results from classification tasks

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

PubDNA Finder in a Nutshell. Searching the Life Sciences Literature with Sequences of Nucleic Acids

Biomedical researchers and clinicians working with molecular technologies in routine clinical practice often need to review the available literature to gather information regarding specific sequences of nucleic acids. This includes, for instance, finding articles related to a concrete DNA sequence, or identifying empirically-validated primer/probe sequences to evaluate the presence of different micro-organisms. Unfortunately, these hard and time-consuming tasks often need to be manually performed by researchers themselves since no publicly available biomedical literature search engine, e.g. PubMed, PubMed Central (PMC), etc., provides the required search functionalities. In this article, we describe PubDNA Finder, a web service that enables users to perform advanced searches on PubMed Central-indexed full text articles with sequences of nucleic acid

UTwente does Brave New Tasks for MediaEval 2012: Searching and Hyperlinking

In this paper we report our experiments and results for the brave new searching and hyperlinking tasks for the MediaEval Benchmark Initiative 2012. The searching task involves nding target video segments based on a short natural language sentence query and the hyperlinking task involves nding links from the target video segments to other related video segments in the collection using a set of anchor segments in the videos that correspond to the textual search queries. To nd the starting points in the video, we only used speech transcripts and metadata as evidence source, however, other visual features (for e.g., faces, shots and keyframes) might also aect results for a query. We indexed speech transcripts and metadata, furthermore, the speech transcripts were indexed at speech segment level and at sentence level to improve the likelihood of nding jump-in-points. For linking video segments, we computed k-nearest neighbours of video segments using euclidean distance