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Functional Applications of Text Analytics Systems

Steven Simske | Marie Vans
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A01=Marie Vans
A01=Steven Simske
ABM
advanced text analytics applications
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Antibody Residues
Author_Marie Vans
Author_Steven Simske
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Category1=Non-Fiction
Category=UYQ
COP=Denmark
Data Sets
Delivery_Pre-order
document clustering
ensemble learning methods
eq_bestseller
eq_computing
eq_isMigrated=2
eq_nobargain
eq_non-fiction
Face Emotion Recognition
Fergus Falls
French Speech
Ground Truthing
Incremental Step Size
information retrieval
knowledge discovery systems
Language_English
Machine Learning
natural language processing
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PA=Temporarily unavailable
Peak Accuracy
Penalty Score
Performing Text Analytics
Price_€100 and above
PS=Active
Query Set
Reading Order
Round Trips
Russian Speech
softlaunch
Statistical MT
Summarization Approaches
term frequency analysis
Text Analytic Systems
Text Analytic Tasks
Training Data
Translation Accuracy
Translation Engine
Vehicle Count

Product details

  • ISBN 9788770223430
  • Weight: 580g
  • Dimensions: 156 x 234mm
  • Publication Date: 31 Jan 2021
  • Publisher: River Publishers
  • Publication City/Country: DK
  • Product Form: Hardback
  • Language: English
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Description

Text analytics consist of the statistics about a text element, which includes the word count, the word histogram, and the word frequency histogram. Most text documents of value are related to other—sometimes many other—documents, and so analytics describing the relative frequency of terms in a document compared to its peers are important for defining key words (tagging, labeling, indexing), search-responsive terms (query terms), and compressed versions of the documents (key words, summary, etc.).This clearly written text explains the functional applications of search, translation, optimization, and learning with regard to text analytics. Generation of analytics is aided by a hybrid, ensemble, or other combinatorial approach in which two or more effective analytic processes are used simultaneously, and their outputs combined to form a better “consensus”. Additional value to the preservation of the information is provided through these methods. Also, since they encompass capabilities of two or more knowledge-generating systems, they can create a “superset” of access points to the data generated. The book also describes the role of functional approaches in the testing and configuration of these systems.
About Marie Vans | Steven Simske
Steve Simske is a Professor in the Systems Engineering Department at Colorado State University (CSU), where he leads research on analytics, cybersecurity, sensing, imaging, and robotics. A former Fellow in HP Labs, Steve was in the computer and printing industries for 23 years before joining CSU in 2018. He holds more than 200 US Patents and has more than 450 publications. This is his fourth book. Marie Vans is a senior research scientist at HP Labs in Fort Collins, currently working in the AI & Emerging Compute Lab where she is focused on developing virtual reality simulations for education, product introduction, and analytics associated with educational experiences in VR. She is also on the faculty of the San José State University, School of Information. She holds a Ph.D. and M.S. in Computer Science from Colorado State, an MLIS from San José State University, and has more than 55 published papers and 35 U.S. granted patents.

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