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Textual Data

by S. Gowri, G. S. An, Ha Mala
"... Abstract There are numerous imperative digital text based proofs, some of which are SMS (Short Message Services), messages, mails, chat logs, etc. The person who researches a case is fundamentally overflowed with information and he needs to invest all his profitable examination time, examining throu ..."
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through the loud indexed lists and experiencing unimportant query items. Hence a system is initiated using digital textual data mining standards for configuration and execution, which enhances IIR (Intelligent Information Retrieval) viability in digital forensics. The framework analyzes the input corpus

WEBSOM for Textual Data Mining

by Krista Lagus, Timo Honkela, Samuel Kaski, Teuvo Kohonen - Artificial Intelligence Review , 1999
"... New methods that axe user-friendly and efficient axe needed for guidance among the masses of textual information available in the Internet and the World Wide Web. We have developed a method and a tool called the WEBSON which utilizes the self-organizing map algorithm (SON) for organizing laxge colle ..."
Abstract - Cited by 29 (4 self) - Add to MetaCart
organizing, visualizing, seaxching, categorizing and filtering textual data. Furthermore, we discuss and illustrate with examples how document maps can aid in these situations. An example is presented where a document map is utilized as a tool for visualizing and filtering a stream of incoming electronic

Textual Data Representation

by Mikaela Keller, Samy Bengio, Mikaela Keller, Samy Bengio , 2003
"... Abstract. We address in this report the problem of representing formally textual data. First, this problem is replaced in the context of automatic text processing. Then, the weaknesses of the basic document representation, i.e. the bag-of-words representation, are explained and some state-of-the-art ..."
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Abstract. We address in this report the problem of representing formally textual data. First, this problem is replaced in the context of automatic text processing. Then, the weaknesses of the basic document representation, i.e. the bag-of-words representation, are explained and some state

Mining Textual Data in Croatian

by Bojana Dalbelo Bašić, Boris Bereček, Ana Cvitaš
"... Abstract – Business intelligence systems find textual data a very useful source of information. Text processing algorithms and systems in English and other world languages are well developed, which is not the case with Croatian language. This paper explores the applicability of existing systems and ..."
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Abstract – Business intelligence systems find textual data a very useful source of information. Text processing algorithms and systems in English and other world languages are well developed, which is not the case with Croatian language. This paper explores the applicability of existing systems

TEXTUAL DATA OF VIDEOS

by Prof Dr, Adnan Yazıcı, Asst Prof, Dr. Ahmet, Asst Prof, Dr. Sinan Kalkan, Asst Prof, Dr. Mustafa Sert , 2012
"... Date: I hereby declare that all information in this document has been obtained and presented in accordance with academic rules and ethical conduct. I also declare that, as required by these rules and conduct, I have fully cited and referenced all material and results that are not original to this wo ..."
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Date: I hereby declare that all information in this document has been obtained and presented in accordance with academic rules and ethical conduct. I also declare that, as required by these rules and conduct, I have fully cited and referenced all material and results that are not original to this work.

Learning Causality from Textual Data

by Kira Radinsky, Sagie Davidovich, Shaul Markovitch
"... We present a new methodology for modeling and predicting future events through machine learning and data mining techniques from textual data. Modeled events span across varied domains including politics, economy and society. The model employs human-style prediction techniques such as causality infer ..."
Abstract - Cited by 1 (0 self) - Add to MetaCart
We present a new methodology for modeling and predicting future events through machine learning and data mining techniques from textual data. Modeled events span across varied domains including politics, economy and society. The model employs human-style prediction techniques such as causality

Latent Semantic Analysis of Textual Data

by Preslav Nakov - In Proceedings of CompSysTech’2000 , 2000
"... Latent Semantic Analysis of Text Information The paper presents an overview of the usage of LSA for analysis of textual data. The mathematical apparatus is explained in brief and special attention if pointed on the key parameters that influence the quality of the results obtained. The potential of L ..."
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Latent Semantic Analysis of Text Information The paper presents an overview of the usage of LSA for analysis of textual data. The mathematical apparatus is explained in brief and special attention if pointed on the key parameters that influence the quality of the results obtained. The potential

Detecting Emerging Concepts in Textual Data Mining

by William M. Pottenger, Ting-hao Yang - In Computational Information Retrieval , 2001
"... This article summarizes our research to date in the automatic identification of emerging trends in textual data. Applications are numerous: the detection of trends in warranty repair claims, for example, is of genuine interest to NCSA industrial partners Caterpillar and Boeing. Technology forecastin ..."
Abstract - Cited by 18 (4 self) - Add to MetaCart
This article summarizes our research to date in the automatic identification of emerging trends in textual data. Applications are numerous: the detection of trends in warranty repair claims, for example, is of genuine interest to NCSA industrial partners Caterpillar and Boeing. Technology

Methodologies for Trend Detection in Textual Data Mining

by Soma Roy, David Gevry, William M. Pottenger , 2001
"... We present two methodologies for the detection of emerging trends in the area of textual data mining. These manual methods are intended to help us improve the performance of our existing fully automatic trend detection system [3]. ..."
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We present two methodologies for the detection of emerging trends in the area of textual data mining. These manual methods are intended to help us improve the performance of our existing fully automatic trend detection system [3].

Learning to Predict from Textual Data

by Kira Radinsky, Sagie Davidovich, Shaul Markovitch
"... Given a current news event, we tackle the problem of generating plausible predictions of future events it might cause. We present a new methodology for modeling and predicting such future news events using machine learning and data mining techniques. Our Pundit algorithm generalizes examples of caus ..."
Abstract - Cited by 4 (0 self) - Add to MetaCart
Given a current news event, we tackle the problem of generating plausible predictions of future events it might cause. We present a new methodology for modeling and predicting such future news events using machine learning and data mining techniques. Our Pundit algorithm generalizes examples
Results 1 - 10 of 4,094