3.5 Databases, Knowledge Discovery, Information Retrieval, and Web Mining

2006 ◽  
Keyword(s):  
Information Retrieval ◽  
Knowledge Discovery ◽  
Web Mining

An Overview of Biological Data Mining

Biotechnology ◽  
2019 ◽  
pp. 120-139
Author(s):  
Seetharaman Balaji
Keyword(s):  
Data Mining ◽  
Information Retrieval ◽  
Biological Networks ◽  
Web Mining ◽  
Biological Data ◽  
Biological Research ◽  
Digital Repository ◽  
Domain Specific ◽  
Novice Learner ◽  
Integration Data

The largest digital repository of information, the World Wide Web keeps growing exponentially and calls for data mining services to provide tailored web experiences. This chapter discusses the overview of information retrieval, knowledge discovery and data mining. It reviews the different stages of data mining and introduces the wide spread biological databanks, their explosion, integration, data warehousing, information retrieval, text mining, text repositories for biological research publications, domain specific search engines, web mining, biological networks and visualization, ontology and systems biology. This chapter also illustrates some technical jargon with picture analogy for a novice learner to understand the concepts clearly.

Need of Intelligent Search in Dynamic Social Network

2018 ◽  
pp. 144-157
Author(s):  
Shailendra Kumar Sonkar ◽  
Vishal Bhatnagar ◽  
Rama Krishna Challa
Keyword(s):  
Information Retrieval ◽  
Social Network ◽  
Web Mining ◽  
Relevant Information ◽  
Future Research ◽  
Intelligent Search ◽  
Dynamic Social Network ◽  
The Social ◽  
Intelligent Information ◽  
Conference Papers

The user of dynamic social network does not require irrelevant and vast amount of information during a search. A need of an intelligent search is required to get the reduced, filtered and relevant information that is achieved using an intelligent information retrieval and web mining. In this paper, identification and description of facts related to needs of an intelligent search in dynamic social network has been done by the authors after the deep and thorough study conducted on several journal and conference papers that are scattered on different electronic databases globally. The usage of intelligent agent for effective information retrieval from the social network site is a very emerging area and it will help the users to find the relevant and concerned information quickly and efficiently. The findings of the authors will help researchers and scholars who are already working in this area to get the relevant information in the direction of future research.

Mastering Web Mining and Information Retrieval in the Digital Age

2017 ◽  
pp. 1-28 ◽  
Author(s):  
Kijpokin Kasemsap
Keyword(s):  
Information Retrieval ◽  
Organizational Performance ◽  
User Interfaces ◽  
Web Mining ◽  
Digital Age ◽  
Mass Storage ◽  
Web Data ◽  
Time Saving ◽  
Storage Devices ◽  
Collaborative Information Retrieval

This chapter aims to master web mining and Information Retrieval (IR) in the digital age, thus describing the overviews of web mining and web usage mining; the significance of web mining in the digital age; the overview of IR; the concept of Collaborative Information Retrieval (CIR); the evaluation of IR systems; and the significance of IR in the digital age. Web mining can contribute to the increase in profits by selling more products and by minimizing costs. Web mining is the application of data mining techniques to discover the interesting patterns from web data in order to better serve the needs of web-based multifaceted applications. Mining web data can improve the personalization, create the selling opportunities, and lead to more profitable relationships with customers in global business. Web mining techniques can be applied with the effective analysis of the clearly understood business needs and requirements. Web mining builds the detailed customer profiles based on the transactional data. Web mining is used to create the personalized search engines which can recognize the individuals' search queries by analyzing and profiling the web user's search behavior. IR is the process of obtaining relevant information from a collection of informational resources. IR has considerably changed with the expansion of the Internet and the advent of modern and inexpensive graphical user interfaces and mass storage devices. The effective IR system, including an active indexing system, not only decreases the chances that information will be misfiled but also expedites the retrieval of information. Regarding IR utilization, the resulting time-saving benefit increases office efficiency and productivity while decreasing stress and anxiety. Most IR systems provide the advanced searching capabilities that allow users to create the sophisticated queries. The chapter argues that applying web mining and IR has the potential to enhance organizational performance and reach strategic goals in the digital age.

An Overview of Biological Data Mining

2017 ◽  
pp. 130-154
Author(s):  
Seetharaman Balaji
Keyword(s):  
Data Mining ◽  
Information Retrieval ◽  
Biological Networks ◽  
Web Mining ◽  
Biological Data ◽  
Biological Research ◽  
Digital Repository ◽  
Domain Specific ◽  
Novice Learner ◽  
Integration Data

The largest digital repository of information, the World Wide Web keeps growing exponentially and calls for data mining services to provide tailored web experiences. This chapter discusses the overview of information retrieval, knowledge discovery and data mining. It reviews the different stages of data mining and introduces the wide spread biological databanks, their explosion, integration, data warehousing, information retrieval, text mining, text repositories for biological research publications, domain specific search engines, web mining, biological networks and visualization, ontology and systems biology. This chapter also illustrates some technical jargon with picture analogy for a novice learner to understand the concepts clearly.

Enhancing Web Search through Query Log Mining

2011 ◽  
pp. 438-442
Author(s):  
Ji-Rong Wen
Keyword(s):  
Information Retrieval ◽  
Search Engine ◽  
Web Mining ◽  
Web Search ◽  
Information Source ◽  
Query Log ◽  
Additional Information ◽  
Query Logs ◽  
Query Log Mining ◽  
The Web

Web query log is a type of file keeping track of the activities of the users who are utilizing a search engine. Compared to traditional information retrieval setting in which documents are the only information source available, query logs are an additional information source in the Web search setting. Based on query logs, a set of Web mining techniques, such as log-based query clustering, log-based query expansion, collaborative filtering and personalized search, could be employed to improve the performance of Web search.

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