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2011-04-19
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kd-tree - Wikipedia, the free encyclopedia
In computer science, a kd-tree (short for k-dimensional tree) is a space-partitioning data structure for organizing points in a k-dimensional space. kd-trees are a useful data structure for several applications, such as searches involving a multidimensional search key (e.g. range searches and nearest neighbour searches).
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2011-04-15
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Accepted Papers -- W3C Workshop on Web Tracking and User Privacy
This workshop serves to establish a common view on possible Recommendation-track work in the Web privacy and tracking protection space at W3C, and on the coordination needs for such work.
The workshop is expected to attract a broad set of stakeholders, including implementers from the mobile and desktop space, large and small content delivery providers, advertisement networks, search engines, policy and privacy experts, experts in consumer protection, and other parties with an interest in Web tracking technologies, including the developers and operators of Services on the Web that make use of tracking technologies for purposes other than to behavioral advertising.
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2011-01-12
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GeoNetwork opensource
"GeoNetwork is a catalog application to manage spatially referenced resources. It provides powerful metadata editing and search functions as well as an embedded interactive web map viewer. It is currently used in numerous Spatial Data Infrastructure initiatives across the world."
Implements INSPIRE - integrates AGROVOC?
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2010-11-23
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RDF Data Analysis with Activation Patterns
RDF data can be analyzed with various query languages such as SPARQL
or SeRQL. Due to their nature these query languages do not support fuzzy queries.
In this paper we present a new method that transforms the information presented
by subject-relation-object relations within RDF data into Activation Patterns. These
patterns represent a common model that is the basis for a number of sophisticated
analysis methods such as semantic relation analysis, semantic search queries, unsuper-
vised clustering, supervised learning or anomaly detection. In this paper, we explain
the Activation Patterns concept and apply it to an RDF representation of the well
known CIA World Factbook.
Peter Teufl and Günther Lackner
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2010-11-12
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A SURVEY OF EIGENVECTOR METHODS FOR WEB INFORMATION RETRIEVAL
Web information retrieval is significantly more challenging than traditional well controlled,
small document collection information retrieval. One main difference between traditional information retrieval and Web information retrieval is the Web's hyperlink structure. This structure has been exploited by several of today's leading Web search engines, particularly Google and Teoma. In this survey paper, we focus on Web information retrieval methods that use eigenvector
computations, presenting the three popular methods of HITS, PageRank, and SALSA.
AMY N. LANGVILLE, CARL D. MEYER
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2010-11-09
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A Node Indexing Scheme for Web Entity Retrieval
Now motivated also by the partial support of major search engines, hundreds of millions of documents are being published on the web embedding semi-structured data in RDF, RDFa and Microformats. This scenario calls for novel information search systems which provide effective means of retrieving relevant semi-structured information. In this paper, we present an entity retrieval system designed to provide entity search capabilities over datasets as large as the entire Web of Data. Our system supports full-text search, semi-structural queries and top-k query results while exhibiting a concise index and efficient incremental updates. We advocate the use of a node indexing scheme and show that it offers a good compromise between query expressiveness, query processing time and update complexity in comparison to three other indexing techniques. We then demonstrate how such system can effectively answer queries over 10 billion triples on a single commodity machine.
Renaud Delbru, Nickolai Toupikov, Michele Catasta, Giovanni Tummarello
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2010-11-09
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Using Naming Authority to Rank Data and Ontologies for Web Search
The focus of web search is moving away from returning relevant documents towards returning structured data as results to user queries. A vital part in the architecture of search engines are link-based ranking algorithms, which however are targeted towards hypertext documents. Existing ranking algorithms for structured data, on the other hand, require manual input of a domain expert and are thus not applicable in
cases where data integrated from a large number of sources exhibits enormous variance in vocabularies used. In such environments, the authority of data sources is an important signal that the ranking algorithm has to take into account. This paper presents algorithms for prioritising data returned by queries over web datasets expressed in RDF. We introduce the notion of naming authority which provides a correspondence between identifiers and the sources which can speak authoritatively for these identifiers. Our algorithm uses the original PageRank method to assign authority values to data sources based on a naming authority graph, and then propagates the authority values to identifiers referenced in the sources. We conduct performance and quality evaluations of the method on a large web dataset. Our method is schema-independent, requires no manual input, and has applications in search, query processing, reasoning, and user interfaces over integrated datasets.
Andreas Harth, Sheila Kinsella, Stefan Decker
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2010-09-27
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Implementing LinkedIn Faceted Search
Nice description and linked to open-source projects from linkedin team.
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2010-09-21
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Faceted Wikipedia Search
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2010-08-18
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Friend of a friend (FOAF) search engine
A FOAF search engine.
