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Efficient incremental density-based algorithm for clustering large datasets
2015
Alexandria Engineering Journal
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In this paper, an enhanced version of the incremental DBSCAN algorithm is introduced for incrementally building and updating arbitrary shaped clusters in large datasets. ...
The proposed algorithm enhances the incremental clustering process by limiting the search space to partitions rather than the whole dataset which results in significant improvements in the performance ...
In this paper, an incremental density-based clustering algorithm is introduced for incrementally building and updating clusters in the dataset. ...
doi:10.1016/j.aej.2015.08.009
fatcat:ovbelsx22jgdpplvj2tuujqzuy
Recent Trends in Incremental Clustering: A Review
2017
IOSR Journal of Computer Engineering
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The paper is original with respect to one aspect that is, it provides a complete overview that is fully devoted to evolutionary algorithms for incremental clustering. ...
A number of references are provided that describe applications of evolutionary algorithms for incremental clustering in different domains, such as human activity detection, online fault detection, information ...
A single-pass clustering algorithm is used in order to generate pre-clustered results for the next stage. ...
doi:10.9790/0661-1901011924
fatcat:nbtn2ablcjagzooji5jlsgfspi
An incremental clustering crawler for community-limited search
2009
2009 Second International Conference on the Applications of Digital Information and Web Technologies
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We propose an incremental clustering crawler, a novel algorithm for finding communities for community-limited search in the web. ...
An apparent disadvantage is that the resulting clusters are not optimal since the algorithm does not have all the crawled sites available at the time of clustering. ...
An Incremental Clustering Crawler
Algorithm As mentioned above, the incremental clustering crawler (ICC) performs clustering while web pages are being collected by a crawler. ...
doi:10.1109/icadiwt.2009.5273940
fatcat:tsk7wdj5qbhopglga6yfd5bfs4
Exploratory Web Searching with Dynamic Taxonomies and Results Clustering
[chapter]
2009
Lecture Notes in Computer Science
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On-line results clustering is useful for providing users with overviews of the results and thus allowing them to restrict their focus to the desired parts. ...
This combination results to an effective, flexible and efficient exploration experience. ...
Incremental Evaluation Algorithm Here we present an incremental approach for exploiting past computations and results. Let A f be the objects of the current focus. ...
doi:10.1007/978-3-642-04346-8_12
fatcat:mbe7lgdoybfyfanuniv5iojslu
Computational analysis of incremental clustering approaches for Large Data
2021
International journal of computers and communications
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In this paper, an incremental approach for clustering is introduced using K-means and DBSCAN to handle the new datasets dynamically updated in the database in an interval. ...
These two approaches of clustering are the classical methods for efficient clustering but underperform when the data is updated frequently in the databases so, the incremental or gradual clustering approaches ...
An incremental DBSCAN based technique was Introduced by [5] for incrementally building and updating clusters in the dataset by incrementally partitioning the dataset to reduce the search space of the ...
doi:10.46300/91013.2021.15.3
fatcat:zto4mmguqbfl5ggojszgjswsom
Keyword search on external memory data graphs
2008
Proceedings of the VLDB Endowment
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We compare our algorithms with a virtual memory approach on several real data sets. Our experimental results show significant benefits in terms of reduction in IO due to our algorithms. ...
are likely to give good results. ...
Incremental Expansion Algorithm As for iterative search, the incremental expansion algorithm also performs keyword search on the multi-granular graph. ...
doi:10.14778/1453856.1453982
fatcat:u4xn6hqyrfayvotw3tsqui6coy
Efficient Computation of Jointree Bounds for Systematic MAP Search
2009
International Joint Conference on Artificial Intelligence
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Since almost all search time is spent computing the jointree bounds, we introduce an efficient method for computing these bounds incrementally. ...
We point out that, using a static variable ordering, it is only necessary to compute relevant upper bounds at each search step, and it is also possible to cache potentials of the jointree for efficient ...
Figure 2 (a) shows an example search tree for three MAP variables. ...
dblp:conf/ijcai/YuanH09
fatcat:wmi54dpltjfxpkrzlp7naegzya
Analysis of Chinese Patents associated with Incremental Clustering Algorithms: A Review
2022
Journal of Computing Research and Innovation
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To achieve learning from such dynamic data sources, incremental clustering algorithms are used mandatorily. ...
Due consideration of the prior art search, the author found that China the country of registration of the application extensively contributes to the intellectual property related to incremental clustering ...
The Incremental-Clustering (IC) is an elite category of clustering algorithms. ...
doi:10.24191/jcrinn.v7i1.266
fatcat:ved3pjqqrvgzzpknpsmki6vs2a
Dynamic Indexing for Incremental Entity Resolution in Data Integration Systems
2017
Proceedings of the 19th International Conference on Enterprise Information Systems
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In this context, this work proposes an indexing technique for incremental Entity Resolution processes. ...
We performed some experiments and the time spent for storing, accessing and updating the indexes was measured. ...
(ii) Best-Case: uses an incremental algorithm, assuming that all tuples from the query result were indexed. ...
doi:10.5220/0006251801850192
dblp:conf/iceis/VieiraLS17
fatcat:za3drkm7gfahflztwrs3lnawmq
Scalable clustering of news search results
2011
Proceedings of the fourth ACM international conference on Web search and data mining - WSDM '11
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In this paper, we present a system for clustering the search results of a news search engine. ...
We propose novel techniques for clustering the search results in realtime. ...
CONCLUSIONS AND FUTURE WORK In this paper, we presented an overall system for clustering news search results. ...
doi:10.1145/1935826.1935918
dblp:conf/wsdm/VadrevuTRPDSCZ11
fatcat:wz6rd7osxjccdldyakftvw6azy
Segmentation by Incremental Clustering
2015
International Journal of Computer Applications
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Clusters c. Segmentation Figure 1: Segmentation by incremental clustering ABSTRACT A method for unsupervised segmentation by incremental clustering is introduced. ...
Correlation clustering is to keep away from pre-definition for number of clusters and incremental approach is to avoid re-clustering that is needed in iterative methods. ...
An incremental clustering algorithm for data mining was developed by Ester et al. Algorithm DBSCAN in [13] is a density-based and partition clustering. ...
doi:10.5120/19591-1360
fatcat:qdxd3ueqmndcdawcawt5taxgqi
High-Dimensional Similarity Search Using Data-Sensitive Space Partitioning
[chapter]
2006
Lecture Notes in Computer Science
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Our quest is for a solution with an efficient and scalable search, acceptable dataloading time, and the ability to work on incremental loads of data. ...
A new space partitioning method is proposed along with a new algorithm for exact similarity search in high-dimensional spaces. ...
For best results, the database system should employ a genuine clustering algorithm for this purpose. ...
doi:10.1007/11827405_72
fatcat:2apjccuijfc4rnnf4tcpgbh55e
Relevance feedback with a small number of relevance judgements
2000
Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval - SIGIR '00
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The use of incremental relevance feedback and document clustering were investigated in an relevance feedback environment in which the number of relevance judgements was quite small. ...
To overcome this problem, a query-biased clustering algorithm was developed and shown to be effective. ...
Clustering of the initial search results was reported to be effective for subsequent pseudo relevance feedback [3] . ...
doi:10.1145/345508.345538
dblp:conf/sigir/Iwayama00
fatcat:w6oorgmzi5gdvdcilt5jlqopii
Web document clustering
1998
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval - SIGIR '98
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The IR community has explored document clustering as an alternative method of organizing retrieval results, but clustering has yet to be deployed on the major search engines. ...
To satisfy the stringent requirements of the Web domain, we introduce an incremental, linear time (in the document collection size) algorithm called Suffix Tree Clustering (STC), which creates clusters ...
Karp and Zhenya Sigal for their contributions to this research. We thank Jody Daniels, Marti Hearst, David Lewis and Yoelle Maarek for commenting on earlier draft of this paper. ...
doi:10.1145/290941.290956
dblp:conf/sigir/ZamirE98
fatcat:2vz7rideiva2fglnbycymehehi
An Incremental K-means algorithm
2004
Proceedings of the Institution of mechanical engineers. Part C, journal of mechanical engineering science
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The scheme, which is an incremental version of the K-means algorithm, involves adding cluster centres one by one as clusters are being formed. ...
The paper presents test results to demonstrate the efficacy of the proposed algorithm. ...
The MS was received on 20 August 2003 and was accepted after revision for publication on 26 March 2004. ...
doi:10.1243/0954406041319509
fatcat:k54rrz5iefarpb6icvwt62gz34
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