AKSHR: A novel framework for a Domain-specific Hidden Web Crawler

2010 ◽  
Author(s):  
Komal Kumar Bhatia ◽  
A.K. Sharma ◽  
Rosy Madaan
Keyword(s):  
Web Crawler ◽  
Domain Specific ◽  
Hidden Web

A Framework for Incremental Domain-Specific Hidden Web Crawler

2010 ◽  
pp. 412-422 ◽  
Author(s):  
Rosy Madaan ◽  
Ashutosh Dixit ◽  
A. K. Sharma ◽  
Komal Kumar Bhatia
Keyword(s):  
Web Crawler ◽  
Domain Specific ◽  
Hidden Web

Design of a Least Cost (LC) Vertical Search Engine Based on Domain Specific Hidden Web Crawler

The Dark Web ◽  
2018 ◽  
pp. 319-333
Author(s):  
Sudhakar Ranjan ◽  
Komal Kumar Bhatia
Keyword(s):  
Search Engine ◽  
Human Life ◽  
Experimental Result ◽  
Web Crawler ◽  
Domain Specific ◽  
Hidden Web ◽  
Vertical Search ◽  
Communication Time ◽  
Vertical Search Engine ◽  
Domain Term

Now days with the advent of internet technologies and ecommerce the need for smart search engine for human life is rising. The traditional search engines are not intelligent as well as smart and thus lead to the rise in searching costs. In this paper, architecture of a vertical search engine based on the domain specific hidden web crawler is proposed. To make a least cost vertical search engine improvement in the following techniques like: searching, indexing, ranking, transaction and query interface are suggested. The domain term analyzer filters the useless information to the maximum extent and finally provides the users with high precision information. Through the experimental result it is shown that the system works on accelerating the access, computation, storage, communication time, increased efficiency and work professionally.

Design of a Least Cost (LC) Vertical Search Engine based on Domain Specific Hidden Web Crawler

2017 ◽  
Vol 7 (2) ◽  
pp. 19-33
Author(s):  
Sudhakar Ranjan ◽  
Komal Kumar Bhatia
Keyword(s):  
Search Engine ◽  
Human Life ◽  
Experimental Result ◽  
Web Crawler ◽  
Domain Specific ◽  
Hidden Web ◽  
Vertical Search ◽  
Communication Time ◽  
Vertical Search Engine ◽  
Domain Term

Now days with the advent of internet technologies and ecommerce the need for smart search engine for human life is rising. The traditional search engines are not intelligent as well as smart and thus lead to the rise in searching costs. In this paper, architecture of a vertical search engine based on the domain specific hidden web crawler is proposed. To make a least cost vertical search engine improvement in the following techniques like: searching, indexing, ranking, transaction and query interface are suggested. The domain term analyzer filters the useless information to the maximum extent and finally provides the users with high precision information. Through the experimental result it is shown that the system works on accelerating the access, computation, storage, communication time, increased efficiency and work professionally.

scholarly journals Design of a Parallel and Scalable Crawler for the Hidden Web

2022 ◽  
Vol 12 (1) ◽  
pp. 0-0
Keyword(s):  
Experimental Results ◽  
Web Pages ◽  
Web Crawler ◽  
Huge Amount ◽  
Web Databases ◽  
Specific Approach ◽  
Amount Of Information ◽  
Domain Specific ◽  
Hidden Web ◽  
Enormous Amount

The WWW contains huge amount of information from different areas. This information may be present virtually in the form of web pages, media, articles (research journals / magazine), blogs etc. A major portion of the information is present in web databases that can be retrieved by raising queries at the interface offered by the specific database and is thus called the Hidden Web. An important issue is to efficiently retrieve and provide access to this enormous amount of information through crawling. In this paper, we present the architecture of a parallel crawler for the Hidden Web that avoids download overlaps by following a domain-specific approach. The experimental results further show that the proposed parallel Hidden web crawler (PSHWC), not only effectively but also efficiently extracts and download the contents in the Hidden web databases

scholarly journals SIMHAR - Smart Distributed Web Crawler for the Hidden Web Using SIM+Hash and Redis Server

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 117582-117592
Author(s):  
Sawroop Kaur ◽  
G. Geetha
Keyword(s):  
Web Crawler ◽  
Hidden Web

Clustering-Based Topical Web Crawling for Topic-Specific Information Retrieval Guided by Incremental Classifier

2015 ◽  
Vol 25 (01) ◽  
pp. 147-168 ◽  
Author(s):  
Tao Peng ◽  
Lu Liu
Keyword(s):  
Information Retrieval ◽  
Contextual Information ◽  
Specific Information ◽  
Specific Class ◽  
Web Page ◽  
Web Crawler ◽  
Web Page Classification ◽  
Domain Specific ◽  
Anchor Text ◽  
Page Classification

Today more and more information on the Web makes it difficult to get domain-specific information due to the huge amount of data sources and the keywords that have few features. Anchor texts, which contain a few features of a specific topic, play an important role in domain-specific information retrieval, especially in Web page classification. However, the features contained in anchor texts are not informative enough. This paper presents a novel incremental method for Web page classification enhanced by link-contexts and clustering. Directly applying the vector of anchor text to a classifier might not get a good result because of the limited amount of features. Link-context is used first to obtain the contextual information of the anchor text. Then, a hierarchical clustering method is introduced to cluster feature vectors and content unit, which increases the length of a feature vector belonging to one specific class. Finally, incremental SVM is proposed to get the final classifier and increase the accuracy and efficiency of a classifier. Experimental results show that the performance of our proposed method outperforms the conventional topical Web crawler in Harvest rate and Target recall.

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