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  Browse All Reviews > Information Systems (H) > Information Storage And Retrieval (H.3) > Information Search And Retrieval (H.3.3) > Clustering (H.3.3...)  
  1-10 of 110 Reviews about "Clustering (H.3.3...)": Date Reviewed
  Fast and accurate time-series clustering
Paparrizos J., Gravano L.  ACM Transactions on Database Systems 42(2): 1-49, 2017. Type: Article

Clustering temporal data, namely time series, is a challenging and expensive computational task in terms of accuracy and speed. Despite the fact that a wide variety of time-series clustering algorithms exist in the literature, they remain unsatisf...

Apr 16 2018
  On temporal-constrained sub-trajectory cluster analysis
Pelekis N., Tampakis P., Vodas M., Doulkeridis C., Theodoridis Y.  Data Mining and Knowledge Discovery 31(5): 1294-1330, 2017. Type: Article

The growing popularity of location-enabled tracking devices has triggered a new sense of interest and enthusiasm for creating appropriate datasets or databases, and new approaches for carrying out data analytics. Demand and need for developing cap...

Apr 12 2018
  Big data analytics: methods and applications
Pyne S., Rao B., Rao S.,  Springer International Publishing, New York, NY, 2016. 276 pp. Type: Book (978-8-132236-26-9), Reviews: (1 of 2)

The rapid growth of online information systems, the ease of collecting data across many users, and the potential commercial value of learning about those users have led to growing interest in methods that address data characterized by high volume ...

Sep 26 2017
  Big data analytics: methods and applications
Pyne S., Rao B., Rao S.,  Springer International Publishing, New York, NY, 2016. 276 pp. Type: Book (978-8-132236-26-9), Reviews: (1 of 2)

Big data analytics has generated much research attention in the past decade, focusing on the architectural and methodological challenges of processing enormous datasets and extreme rates of data generation and collection (two of the three “V...

Apr 26 2017
  Beyond entities: promoting explorative search with bundles
Bordino I., Lalmas M., Mejova Y., Van Laere O.  Information Retrieval 19(5): 447-486, 2016. Type: Article

Search results are usually ranked lists of documents relevant to query terms. In this paper, the entity search results are bundled with those beyond the query term, by constructing the entity network where extracted entities and pairwise entity re...

Jan 25 2017
  Co-clustering structural temporal data with applications to semiconductor manufacturing
Zhu Y., He J.  ACM Transactions on Knowledge Discovery from Data 10(4): 1-18, 2016. Type: Article

New improvements in storage, measurement, and control methods in semiconductor engineering are rapidly producing more data. Today, there are valuable tools for monitoring and gathering time-based data for manufacturing devices such as integrated c...

Nov 15 2016
  Distributed and sequential algorithms for bioinformatics
Erciyes K.,  Springer International Publishing, New York, NY, 2015. 367 pp. Type: Book (978-3-319249-64-3)

The analysis of vast amounts of biological data has the potential to significantly impact and aid further development of bioengineering processes that can be used for medical purposes such as the treatment of diseases. Traditionally most bioinform...

Sep 6 2016
  Subspace clustering of data streams: new algorithms and effective evaluation measures
Hassani M., Kim Y., Choi S., Seidl T.  Journal of Intelligent Information Systems 45(3): 319-335, 2015. Type: Article

Recently, much attention has been paid to data that evolve over time, which are usually called data streams. This paper proposes a contribution for comparing the efficiency of different existing subspace clustering algorithms, meaning algorithms t...

Jun 7 2016
  Multidisciplinary approaches to artificial swarm intelligence for heterogeneous computing and cloud scheduling
Wang J., Gong B., Liu H., Li S.  Applied Intelligence 43(3): 662-675, 2015. Type: Article

As business and scientific data have increased dramatically, distributed computing using high-speed networks has become very popular for organizations. From this perspective, this paper is interesting as it presents a security-aware model for such...

Mar 24 2016
  Mixture model averaging for clustering
Wei Y., McNicholas P.  Advances in Data Analysis and Classification 9(2): 197-217, 2015. Type: Article

Clustering is a popular task in data analysis. With a broad range of applications, various clustering approaches have been developed in the literature. These computational methods often result in different clusters from the same dataset. This is n...

Sep 30 2015
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