Matches in SemOpenAlex for { <https://semopenalex.org/work/W2172023103> ?p ?o ?g. }
Showing items 1 to 85 of
85
with 100 items per page.
- W2172023103 endingPage "763" @default.
- W2172023103 startingPage "748" @default.
- W2172023103 abstract "Support vector machines (SVMs) have been adopted by many data mining and information-retrieval applications for learning a mining or query concept, and then retrieving the top-k best matches to the concept. However, when the data set is large, naively scanning the entire data set to find the top matches is not scalable. In this work, we propose a kernel indexing strategy to substantially prune the search space and, thus, improve the performance of top-k queries. Our kernel indexer (KDX) takes advantage of the underlying geometric properties and quickly converges on an approximate set of top-k instances of interest. More importantly, once the kernel (e.g., Gaussian kernel) has been selected and the indexer has been constructed, the indexer can work with different kernel-parameter settings (e.g., /spl gamma/ and /spl sigma/) without performance compromise. Through theoretical analysis and empirical studies on a wide variety of data sets, we demonstrate KDX to be very effective. An earlier version of this paper appeared in the 2005 SIAM International Conference on Data Mining. This version differs from the previous submission in providing a detailed cost analysis under different scenarios, specifically designed to meet the varying needs of accuracy, speed, and space requirements, developing an approach for insertion and deletion of instances, presenting the specific computations as well as the geometric properties used in performing the same, and providing detailed algorithms for each of the operations necessary to create and use the index structure." @default.
- W2172023103 created "2016-06-24" @default.
- W2172023103 creator A5006834844 @default.
- W2172023103 creator A5013545831 @default.
- W2172023103 date "2006-06-01" @default.
- W2172023103 modified "2023-10-16" @default.
- W2172023103 title "KDX: an indexer for support vector machines" @default.
- W2172023103 cites W1693491370 @default.
- W2172023103 cites W2000830496 @default.
- W2172023103 cites W2061122559 @default.
- W2172023103 cites W2097042476 @default.
- W2172023103 cites W2108728387 @default.
- W2172023103 cites W2124351082 @default.
- W2172023103 cites W2128036349 @default.
- W2172023103 cites W2143426320 @default.
- W2172023103 cites W2144407188 @default.
- W2172023103 cites W2145725688 @default.
- W2172023103 cites W2151135734 @default.
- W2172023103 cites W2156909104 @default.
- W2172023103 cites W2169384781 @default.
- W2172023103 cites W4239510810 @default.
- W2172023103 doi "https://doi.org/10.1109/tkde.2006.101" @default.
- W2172023103 hasPublicationYear "2006" @default.
- W2172023103 type Work @default.
- W2172023103 sameAs 2172023103 @default.
- W2172023103 citedByCount "12" @default.
- W2172023103 countsByYear W21720231032012 @default.
- W2172023103 countsByYear W21720231032013 @default.
- W2172023103 countsByYear W21720231032014 @default.
- W2172023103 countsByYear W21720231032015 @default.
- W2172023103 countsByYear W21720231032017 @default.
- W2172023103 crossrefType "journal-article" @default.
- W2172023103 hasAuthorship W2172023103A5006834844 @default.
- W2172023103 hasAuthorship W2172023103A5013545831 @default.
- W2172023103 hasConcept C114614502 @default.
- W2172023103 hasConcept C119857082 @default.
- W2172023103 hasConcept C122280245 @default.
- W2172023103 hasConcept C12267149 @default.
- W2172023103 hasConcept C124101348 @default.
- W2172023103 hasConcept C177264268 @default.
- W2172023103 hasConcept C199360897 @default.
- W2172023103 hasConcept C23123220 @default.
- W2172023103 hasConcept C33923547 @default.
- W2172023103 hasConcept C41008148 @default.
- W2172023103 hasConcept C48044578 @default.
- W2172023103 hasConcept C74193536 @default.
- W2172023103 hasConcept C75165309 @default.
- W2172023103 hasConcept C77088390 @default.
- W2172023103 hasConcept C80444323 @default.
- W2172023103 hasConceptScore W2172023103C114614502 @default.
- W2172023103 hasConceptScore W2172023103C119857082 @default.
- W2172023103 hasConceptScore W2172023103C122280245 @default.
- W2172023103 hasConceptScore W2172023103C12267149 @default.
- W2172023103 hasConceptScore W2172023103C124101348 @default.
- W2172023103 hasConceptScore W2172023103C177264268 @default.
- W2172023103 hasConceptScore W2172023103C199360897 @default.
- W2172023103 hasConceptScore W2172023103C23123220 @default.
- W2172023103 hasConceptScore W2172023103C33923547 @default.
- W2172023103 hasConceptScore W2172023103C41008148 @default.
- W2172023103 hasConceptScore W2172023103C48044578 @default.
- W2172023103 hasConceptScore W2172023103C74193536 @default.
- W2172023103 hasConceptScore W2172023103C75165309 @default.
- W2172023103 hasConceptScore W2172023103C77088390 @default.
- W2172023103 hasConceptScore W2172023103C80444323 @default.
- W2172023103 hasIssue "6" @default.
- W2172023103 hasLocation W21720231031 @default.
- W2172023103 hasOpenAccess W2172023103 @default.
- W2172023103 hasPrimaryLocation W21720231031 @default.
- W2172023103 hasRelatedWork W1513131817 @default.
- W2172023103 hasRelatedWork W2034486678 @default.
- W2172023103 hasRelatedWork W2068048979 @default.
- W2172023103 hasRelatedWork W2094330550 @default.
- W2172023103 hasRelatedWork W2261169288 @default.
- W2172023103 hasRelatedWork W2278722429 @default.
- W2172023103 hasRelatedWork W2368239531 @default.
- W2172023103 hasRelatedWork W2943695427 @default.
- W2172023103 hasRelatedWork W2977967020 @default.
- W2172023103 hasRelatedWork W3033926873 @default.
- W2172023103 hasVolume "18" @default.
- W2172023103 isParatext "false" @default.
- W2172023103 isRetracted "false" @default.
- W2172023103 magId "2172023103" @default.
- W2172023103 workType "article" @default.