Video-Image-Text Content Mining

2017 ◽  
pp. 205-218
Author(s):  
Adjan Abosolaiman
Keyword(s):  
Video Image ◽  
Content Mining ◽  
Text Content

scholarly journals Improved Framework for Bug Severity Classification using N-gram Features with Convolution Neural Network

2019 ◽  
Vol 8 (3) ◽  
pp. 1190-1196
Keyword(s):  
Neural Network ◽  
Feature Selection ◽  
Automated Reasoning ◽  
Research Study ◽  
Convolution Neural Network ◽  
Severity Classification ◽  
Non Linear ◽  
Content Mining ◽  
N Gram ◽  
Text Content

Foreseeing the seriousness/severity of bugs has been established in former research study in order to recover triaging and the process of bug resolution. Therefore, numerous prediction/classification methodologies were developed throughout the years to give an automated reasoning over the seriousness classes. Seriousness or severity is a significant trait of a bug that chooses how rapidly it ought to be measured. It causes designers to comprehend significant bugs on schedule. Though, manual evaluation of severity is a dreary activity and could be off base. This paper comprises of using the text/content mining together along with the use feature selection and bi-grams to improve the order of bugs in six classes. In the proposed methodology the features are refined by the use of convolution layers. Here, the process of convolution-based refining indicates mapping of the features utilizing non-linear methods of all the classes as compared to the existing methodologies.

Text Content Approaches in Web Content Mining

2011 ◽  
pp. 1103-1108
Author(s):  
Víctor Fresno Fernandez ◽  
Luis Magdalena Layos
Keyword(s):  
The Internet ◽  
Global Information ◽  
Sources Of Information ◽  
Web Content ◽  
Global Information System ◽  
The World ◽  
Content Mining ◽  
Text Content ◽  
Source Of Information ◽  
The Web

Since the creation of the Web until now, the Internet has become the greatest source of information available in the world. The Web is defined as a global information system that connects several sources of information by hyperlinks, providing a simple media to publish electronic information and being available to all the connected people.

Solving the Message Classification Problem in Voice Interaction Systems

Vestnik MEI ◽  
2020 ◽  
Vol 5 (5) ◽  
pp. 132-139
Author(s):  
Ivan E. Kurilenko ◽  
◽  
Igor E. Nikonov ◽  
Keyword(s):  
Artificial Intelligence ◽  
Classification Problem ◽  
Subject Area ◽  
Text Messages ◽  
Case Based Reasoning ◽  
Short Text ◽  
Proposed Modification ◽  
Voice Interaction ◽  
Text Content ◽  
Case Based

A method for solving the problem of classifying short-text messages in the form of sentences of customers uttered in talking via the telephone line of organizations is considered. To solve this problem, a classifier was developed, which is based on using a combination of two methods: a description of the subject area in the form of a hierarchy of entities and plausible reasoning based on the case-based reasoning approach, which is actively used in artificial intelligence systems. In solving various problems of artificial intelligence-based analysis of data, these methods have shown a high degree of efficiency, scalability, and independence from data structure. As part of using the case-based reasoning approach in the classifier, it is proposed to modify the TF-IDF (Term Frequency - Inverse Document Frequency) measure of assessing the text content taking into account known information about the distribution of documents by topics. The proposed modification makes it possible to improve the classification quality in comparison with classical measures, since it takes into account the information about the distribution of words not only in a separate document or topic, but in the entire database of cases. Experimental results are presented that confirm the effectiveness of the proposed metric and the developed classifier as applied to classification of customer sentences and providing them with the necessary information depending on the classification result. The developed text classification service prototype is used as part of the voice interaction module with the user in the objective of robotizing the telephone call routing system and making a shift from interaction between the user and system by means of buttons to their interaction through voice.

Traffic incident detection system based on video image processing

2008 ◽  
Vol 28 (7) ◽  
pp. 1886-1889 ◽  
Author(s):  
Qin WANG ◽  
Shan HUANG ◽  
Hong-bin ZHANG ◽  
Quan YANG ◽  
Jian-jun ZHANG
Keyword(s):  
Image Processing ◽  
Detection System ◽  
Video Image ◽  
Incident Detection ◽  
Traffic Incident ◽  
Video Image Processing

Video image character recognition based on stroke-related weight

2013 ◽  
Vol 32 (8) ◽  
pp. 2305-2308
Author(s):  
Chang SU ◽  
Xiao-dong HU ◽  
Bin-fu WANG ◽  
Feng-jun SHANG
Keyword(s):  
Character Recognition ◽  
Video Image
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