Komal Kumar Bhatia

Manvi, Komal Kumar Bhatia, Ashutosh Dixit

Web is a wide term which mainly consists of surface web and hidden web. One can easily access the surface web using traditional web crawlers, but they are not able to crawl the hidden portion of the web. These traditional crawlers retrieve contents from web pages, which are linked by hyperlinks ignoring the information hidden behind form pages, which cannot be extracted using simple hyperlink structure. Thus, they ignore large amount of data hidden behind search forms. This paper emphasizes on the extraction of hidden data behind html search forms. The proposed technique makes use of semantic mapping to fill the html search form using domain specific database. Using semantics to fill various fields of a form leads to more accurate and qualitative data extraction.

Manvi, Komal Kumar Bhatia, Ashutosh Dixit

Deep Web is content hidden behind HTML forms. Since it represents a large portion of the structured, unstructured and dynamic data on the Web, accessing Deep-Web content has been a long challenge for the database community. This paper describes a crawler for accessing Deep-Web using Ontologies. Performance evaluation of the proposed work showed that this new approach has promising results.

Sonali Gupta, Komal Kumar Bhatia

A large amount of data on the WWW remains inaccessible to crawlers of Web search engines because it can only be exposed on demand as users fill out and submit forms. The Hidden web refers to the collection of Web data which can be accessed by the crawler only through an interaction with the Web-based search form and not simply by traversing hyperlinks. Research on Hidden Web has emerged almost a decade ago with the main line being exploring ways to access the content in online databases that are usually hidden behind search forms. The efforts in the area mainly focus on designing hidden Web crawlers that focus on learning forms and filling them with meaningful values. The paper gives an insight into the various Hidden Web crawlers developed for the purpose giving a mention to the advantages and shortcoming of the techniques employed in each.

Sonali Gupta, Komal kumar Bhatia, Pikakshi Manchanda

With the ever proliferating size and scale of the WWW [1] efficient ways of exploring content are of increasing importance. How can we efficiently retrieve information from it through crawling? And in this era of tera and multi-core processors, we ought to think of multi-threaded processes as a serving solution. So, even better how can we improve the crawling performance by using parallel crawlers that work independently? The paper devotes to the fundamental development in the field of parallel crawlers [4] highlighting the advantages and challenges arising from its design. The paper also focuses on the aspect of URL distribution among the various parallel crawling processes or threads and ordering the URLs within each distributed set of URLs. How to distribute URLs from the URL frontier to the various concurrently executing crawling process threads is an orthogonal problem. The paper provides a solution to the problem by designing a framework WebParF that partitions the URL frontier into a several URL queues while considering the various design issues.

Sonali Gupta, Komal Kumar Bhatia

The Hidden Web is the vast repository of informational databases available only through search form interfaces, accessible by therein typing a set of keywords in the search forms. Typically, a Hidden Web crawler is employed to autonomously discover and download pages from the Hidden Web. Traditional hidden web crawlers do not provide the search engines with an optimal search experience because of the excessive number of search requests posed through the form interface so as to exhaustively crawl and retrieve the contents of the target hidden web database. Here in our work, we provide a framework to investigate the problem of optimal search and curtail it by proposing an effective query term selection approach based on the frequency & distribution of terms in the document database. The paper focuses on developing a term-weighing scheme called VarDF (acronym for variable document frequency) that can ease the identification of optimal terms to be used as queries on the interface for maximizing the achieved coverage of the crawler which in turn will facilitate the search engine to have a diversified and expanded index. We experimentally evaluate the effectiveness of our approach on a manually created database of documents in the area of Information Retrieval.