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  Browse All Reviews > Information Systems (H) > Information Storage And Retrieval (H.3) > Information Search And Retrieval (H.3.3)  
 
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  1-10 of 491 Reviews about "Information Search And Retrieval (H.3.3)": Date Reviewed
  Data clustering: theory, algorithms, and applications
Gan G., Ma C., Wu J., SIAM, Philadelphia, PA, 2020. 406 pp.  Type: Book (978-1-611976-32-8)

Data clustering is an unsupervised method of grouping data such that objects in the same cluster are similar and objects in different clusters are distinct. Such techniques have a very diverse span of applicability in areas such as art...

Mar 31 2022
  Mathematics of data science: a computational approach to clustering and classification
Calvetti D., Somersalo E., SIAM, Philadelphia, PA, 2020. 189 pp.  Type: Book (978-1-611976-36-6)

Mathematics is the foundation of data science techniques. With the democratization of data science, almost anyone has access to easy-to-use tools and platforms to get started with data science applications. However, a serious professio...

Oct 7 2021
   Multimodal sentiment analysis
Poria S., Hussain A., Cambria E., Springer International Publishing, New York, NY, 2018. 214 pp.  Type: Book (978-3-319950-18-1)

Bringing emotions and sentiment to virtual (human-centric) environments such as social media further improves decision-making, learning, and communication. This task is rather complex and requires an interdisciplinary approach, includi...

Aug 9 2021
   Exact algorithms via monotone local search
Fomin F., Gaspers S., Lokshtanov D., Saurabh S. Journal of the ACM 66(2): 1-23, 2019.  Type: Article

Many important problems are NP-complete; this means that, unless P = NP, we cannot have a polynomial-time (feasible) algorithm for solving all instances of this problem. For each such problem, there is an exhaustive search algorithm th...

Apr 26 2021
  Modeling information retrieval by formal logic: a survey
Abdulahhad K., Berrut C., Chevallet J., Pasi G. ACM Computing Surveys 52(1): 1-37, 2019.  Type: Article

As the title indicates, formal logic is used for modeling information retrieval (IR). Readers can expect a literature review (of IR models), supported with graphs, mathematical formulas, and examples that lead to some interesting concl...

Apr 12 2021
  Data analysis in bi-partial perspective: clustering and beyond
Owsinski J., Springer International Publishing, New York, NY, 2020. 153 pp.  Type: Book (978-3-030133-88-7)

Owsinski’s book provides an interesting “bi-partial” strategy for analyzing data; it is not only uniquely general, but also successful in building several useful methods to tackle issues related to data an...

Jun 24 2020
   A rapid hybrid clustering algorithm for large volumes of high dimensional data
Rathore P., Kumar D., Bezdek J., Rajasegarar S., Palaniswami M. IEEE Transactions on Knowledge and Data Engineering 31(4): 641-654, 2019.  Type: Article

FensiVAT is a rapid hybrid clustering algorithm that identifies clusters in large datasets characterized by many instances (N) and multiple features (p) in each instance....

Mar 10 2020
  Interactive recommendation with user-specific deep reinforcement learning
Lei Y., Li W. ACM Transactions on Knowledge Discovery from Data 13(6): 1-15, 2019.  Type: Article

Recommender systems are widely used, especially by online applications with a view to enhancing user experience. In most conventional systems, past history of a user’s implicit online behavior is used to derive a new recommen...

Mar 2 2020
  Understanding the needs of searchers with dyslexia
Morris M., Fourney A., Ali A., Vonessen L.  CHI 2018 (Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems, Montreal, Canada, Apr 21-26, 2018) 1-12, 2018.  Type: Proceedings

This paper looks at the web search needs of people with dyslexia, taking into consideration the difficulties they may face in query formulation, result triage, and information extraction. The authors specifically describe the differenc...

Aug 29 2019
  Predicting information retrieval performance
Losee R., Morgan&Claypool Publishers, San Rafael, CA, 2019. 79 pp.  Type: Book (978-1-681734-72-9)

As any Internet user knows, searching is a major activity. Given the size of the total data content available, it is amazing how quickly various search engines are able to provide results. Search providers want to understand the perfor...

Apr 10 2019
 
 
 
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