scholarly journals Toward a web search model: Integrating multitasking, cognitive coordination, and cognitive shifts

2011 ◽  
Vol 62 (8) ◽  
pp. 1446-1472 ◽  
Author(s):  
Jia Tina Du ◽  
Amanda Spink
Keyword(s):  
Web Search ◽  
Search Model

A novel personalized Web search model

2007 ◽  
Vol 12 (5) ◽  
pp. 897-901
Author(s):  
Zhengyu Zhu ◽  
Jingqiu Xu ◽  
Yunyan Tian ◽  
Xiang Ren
Keyword(s):  
Web Search ◽  
Search Model

scholarly journals Opportunities for Remote Collaboration in a Social Web Search Model That Integrates Parents and Children

2014 ◽  
Vol 03 (02) ◽  
pp. 127-133
Author(s):  
Sandra Regina Rocha Silva ◽  
Geraldo Bonorino Xexéo ◽  
Moacir Florentino da Silva
Keyword(s):  
Web Search ◽  
Search Model ◽  
Social Web ◽  
Remote Collaboration ◽  
Parents And Children

scholarly journals Web search model for Automatic Annotation of Tweets in Opinion Mining

2019 ◽  
Vol 9 (2) ◽  
pp. 4848-4852
Keyword(s):  
Sentiment Analysis ◽  
Large Scale ◽  
Web Search ◽  
Opinion Mining ◽  
Systematic Research ◽  
Search Model ◽  
Manual Annotation ◽  
Automatic Annotation ◽  
Automated Annotation ◽  
Annotation Process

In sentiment analysis, annotation is the crucial step of data processing to label the review or sentences as positive, negative, or neutral. An annotation process is usually performed by three key approaches: (i) manual, (ii) crowdsourcing, and (iii) automated annotation. Manual annotation is preferred in most of the literature’s and crowdsourcing tools are used in some of the works. This indicates that there is a scarce of automatic annotation and its service is highly essential to support more systematic research in sentiment analysis. Manual procedures mostly depends on external annotators, resulting in costly and time-consuming processes. Thus, we propose a method for automatic annotation using web search model to dynamically label reviews (positive, negative, or neutral) that are not available in the dictionary. Some research works consider the product opinions from e-commerce sites where most of the texts may not be available in the dictionary, in such cases, the web search model can be used instead of manual annotation. A large-scale opinosis dataset is used to evaluate the accuracy of the algorithms and feasibility of the model. The experimental results indicate that this model outperforms conventional methodologies and therefore we firmly believe it will be useful for current researchers in the field of opinion mining.

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