A Website Mining Model Centered on User Queries

2006 ◽  
pp. 1-17 ◽  
Author(s):  
Ricardo Baeza-Yates ◽  
Barbara Poblete
Keyword(s):  
Mining Model ◽  
User Queries

Design of GA and Ontology based NLP Frameworks for Online Opinion Mining

2019 ◽  
Vol 13 (2) ◽  
pp. 159-165
Author(s):  
Manik Sharma ◽  
Gurvinder Singh ◽  
Rajinder Singh
Keyword(s):  
Genetic Algorithm ◽  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Opinion Mining ◽  
Hybrid Genetic Algorithm ◽  
Online Reviews ◽  
Middle Tier ◽  
Complete Set ◽  
Mining Model

Background: For almost every domain, a tremendous degree of data is accessible in an online and offline mode. Billions of users are daily posting their views or opinions by using different online applications like WhatsApp, Facebook, Twitter, Blogs, Instagram etc. Objective: These reviews are constructive for the progress of the venture, civilization, state and even nation. However, this momentous amount of information is useful only if it is collectively and effectively mined. Methodology: Opinion mining is used to extract the thoughts, expression, emotions, critics, appraisal from the data posted by different persons. It is one of the prevailing research techniques that coalesce and employ the features from natural language processing. Here, an amalgamated approach has been employed to mine online reviews. Results: To improve the results of genetic algorithm based opining mining patent, here, a hybrid genetic algorithm and ontology based 3-tier natural language processing framework named GAO_NLP_OM has been designed. First tier is used for preprocessing and corrosion of the sentences. Middle tier is composed of genetic algorithm based searching module, ontology for English sentences, base words for the review, complete set of English words with item and their features. Genetic algorithm is used to expedite the polarity mining process. The last tier is liable for semantic, discourse and feature summarization. Furthermore, the use of ontology assists in progressing more accurate opinion mining model. Conclusion: GAO_NLP_OM is supposed to improve the performance of genetic algorithm based opinion mining patent. The amalgamation of genetic algorithm, ontology and natural language processing seems to produce fast and more precise results. The proposed framework is able to mine simple as well as compound sentences. However, affirmative preceded interrogative, hidden feature and mixed language sentences still be a challenge for the proposed framework.

An Opinion-Tree Based Flexible Opinion Mining Model

2009 ◽  
Author(s):  
Juling Ding ◽  
Zhongjian Le ◽  
Ping Zhou ◽  
Gensheng Wang ◽  
Wei Shu
Keyword(s):  
Opinion Mining ◽  
Mining Model

The Rapid Development of User Interfaces: Experience with the Wizard of OZ Method

1985 ◽  
Vol 29 (5) ◽  
pp. 470-474 ◽  
Author(s):  
Paul Green ◽  
Lisa Wei-Haas
Keyword(s):  
Personal Computer ◽  
User Interfaces ◽  
Rapid Development ◽  
User Interaction ◽  
Wizard Of Oz ◽  
Iterative Development ◽  
The Subject ◽  
Two Machines ◽  
User Queries

The Wizard of Oz technique is an efficient way to examine user interaction with computers and facilitate rapid iterative development of dialog wording and logic. The technique requires two machines linked together, one for the subject and one for the experimenter. In this implementation the experimenter (the “Wizard”), pretending to be a computer, types in complete replies to user queries or presses function keys to which common messages have been assigned (e.g., Fl=“Help is not available”). The software automatically records the dialog and its timing. This paper provides a detailed description of the first implementation of the Oz paradigm for the IBM Personal Computer. It also includes application guidelines, information which is currently missing from the literature.

Sign in / Sign up

Export Citation Format

Share Document