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This paper describes the Semantic Indexing feature introduced in Oracle Database for indexing unstructured text (document) columns. This capability enables searching for concepts (such as people, places, organizations, and events), in addition to words or phrases, with further options for sense disambiguation and term expansion by consulting knowledge captured in OWL/RDF ontologies. The distinguishing...
The traditional keyword searching mechanism has been unable to meet the needs of current expert knowledge base in searching based on semantic. Considering that the current indexing mechanism in the administration in the area of political affairs vocabulary knowledge management is lack of the ability of query reasoning, this paper combines with the optimizing B+ tree index and inverted index, and proposes...
Current expectations from nowadays information retrieval systems (IRS) have grown beyond the “document contains these terms” requirement that was considered common sense 10–15 years ago. Nowadays systems are expected to return results that are relevant to the intended meaning of the query. In the general IRS usage scenario, the user is not really interested if the returned documents contain or not...
This paper is concerning issues regarding the semantic indexing of resources in a peer to peer network. An important requirement is a good quality of the discovery, i.e. the selection of results very related to a specific request. Keys used for indexing and the corresponding urls of indexed resources are stored in a distributed hash table scattered among the different peers of a community. A key is...
We research ontological indexing and querying as a solution for getting better results in information retrieval, which translates in getting the most relevant documents meeting a query. While most of the research in this field focuses on query reformulation and document representation methods, we focused our research on an ontology-based query guidance system (our proposed OntoSense engine &...
Existing search and content management technology is facing a challenge of locating desired content with the exponentially growing volume of documents. An approach for mitigating this issue is to make use of user-generated tags. However, the improvements are limited because tags are (1) free from context and form, (2) user generated, (3) used for purposes other than description, and (4) often ambiguous...
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