search

Abstract: We introduce the idea of a spatial search engine based on geotags. Geotags are keywords linked to a concrete position. User generated geotags are available from Web 2.0 portals like Flickr1 or Google Maps2. We collected a sample dataset of about 300.000 geotags. In the following we explain a prototype implementation of a search engine and describe how to compute the spatial relevance of a tag. The last section gives an outlook about our research goals in this area and discusses the challenges and possible benefits of integrating semantic information.

 search;  spatial;  flickr;  geocoding;  

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Abstract: The large amount of available information on the Web makes it hard for users to locate resources about particular topics of interest. Traditional search tools, e.g., search engines, do not always successfully cope with this problem, that is, helping users to seek the right information. In the personalized search domain, focused crawlers are receiving increasing attention, as a well-founded alternative to search the Web. Unlike a standard crawler, which traverses the Web downloading all the documents it comes across, a focused crawler is developed to retrieve documents related to a given topic of interest, reducing the network and computational resources. This chapter presents an overview of the focused crawling domain and, in particular, of the approaches that include a sort of adaptivity. That feature makes it possible to change the system behavior according to the particular environment and its relationships with the given input parameters during the search.

 search;  web;  adaptive;  focus;  

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Abstract: The weighted list, known popularly as a tag cloud, has appeared on many popular folksonomy-based web-sites. Flickr, Delicious, Technorati and many others have all featured a tag cloud at some point in their history. However, it is unclear whether the tag cloud is actually useful as an aid to finding information. We conducted an experiment, giving participants the option of using a tag cloud or a traditional search interface to answer various questions. We found that where the information-seeking task required specific information, participants preferred the search interface. Conversely, where the information-seeking task was more general, participants preferred the tag cloud. While the tag cloud is not without value, it is not sufficient as the sole means of navigation for a folksonomy-based dataset. 10.1177/0165551506078083

 search;  tagging;  folksonomy;  tool;  

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Abstract: Social bookmark tools are rapidly emerging on the Web. In such systems users are setting up lightweight conceptual structures called folksonomies. The reason for their immediate success is the fact that no specific skills are needed for participating. At the moment, however, the information retrieval support is limited. We present a formal model and a new search algorithm for folksonomies, called FolkRank, that exploits the structure of the folksonomy. The proposed algorithm is also applied to find communities within the folksonomy and is used to structure search results. All findings are demonstrated on a large scale dataset.

 search;  query;  information-retrieval;  folksonomy;  ranking;  

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Abstract: To help human users and software agents find relevant knowledge on the Semantic Web, the Swoogle search engine discovers, indexes, and analyzes the ontologies and facts that are encoded in Semantic Web documents.

 ontology;  search;  semantic;  information-retrieval;  data-mining;  semanticweb;  

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Abstract: Sorry no abstract available for this article

 metadata;  search;  facets;  image;  

Abstract: XSEarch, a semantic search engine for XML, is presented. XSEarch has a simple query language, suitable for a naive user. It returns semantically related document fragments that satisfy the users query. Query answers are ranked using extended information-retrieval techniques and are generated in an order similar to the ranking. Advanced indexing techniques were developed to facilitate e#cient implementation of XSEarch. The performance of the di#erent techniques as well as the recall...

 XML;  search;  semantic;  database;  information-retrieval;  

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Abstract: The efficient query and extraction of web data is often difficult, because web data does not conform to any data organization standard. In addition, the development of web search technology is still at a relatively early stage. Search engines provide only primitive data query capabilities, and require a detailed syntactic specification to retrieve relevant data. Furthermore, web data exists in a myriad of formats including PDF documents, images, and sound clips that are difficult to be queried. This research proposes a smart web query (SWQ) method for the semantic retrieval of web data. The SWQ method uses domain semantics represented as context ontologies to specify and formulate appropriate web queries to search. This method also relies on semantic search filters to identify and rank relevant web pages semi-automatically. Unlike traditional ontologies that are structured in a hierarchy, terms and their relationships that pertain to a particular domain are organized with a flexible structure by the context ontologies. An SWQ engine is being developed to test the proposed method. Financial trading (e.g. stocks, bonds, unit trusts) is adapted as an example domain (i.e., context) to test and validate the SWQ method and engine.

 ontology;  search;  query;  semantic;  information-retrieval;  data-mining;  semanticweb;  

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Abstract: Sorry no abstract available for this article

 KBGIS;  AI;  search;  

Abstract: Sorry no abstract available for this article

 AI;  search;  

Abstract: As the number of Internet users and the number of accessible Web pages grows, it is becoming increasingly difficult for users to find documents that are relevant to their particular needs. Users must either browse through a large hierarchy of con cepts to find the information for which they are looking or submit a query to a publicly available search engine and wade through hundreds of results, most of them irrelevant. The core of the problem is that whether the user is browsing or searching,...

 ontology;  search;  semantic;  

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