Automated Organic Web Harvesting on Web Data for Analytics

Title

Automated Organic Web Harvesting on Web Data for Analytics

Creator

Jacob L.; Thomas K.T.

Description

Automated Web search and web data extraction has become an inevitable part of research in the area of web mining. The web scraping has immense influence on ecommerce, market research, web indexing and much more. Most of the web information is presented in an unstructured or free format. Web scraping helps every user to retrieve, analyze and use the data suitably according to their requirement. There exist different methodologies for web scraping. Major web scraping tools are rule based systems. In the proposed work, an automated method for web information extraction using Computer Vision is proposed and developed. The proposed automated web scraping method comprises of automated URL extraction virtual extraction of required data and storing the data in a structured format which is useful in market research. 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Source

Lecture Notes in Networks and Systems, Vol-290, pp. 131-141.

Date

2021-01-01

Publisher

Springer Science and Business Media Deutschland GmbH

Subject

Automated scraping; Data scraping; Indexing; Organic web harvesting; SERP pages

Coverage

Jacob L., Christ University, Bangalore, India; Thomas K.T., Christ University, Bangalore, India

Rights

Restricted Access

Relation

ISSN: 23673370; ISBN: 978-981164485-6

Format

Online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1007/978-981-16-4486-3_14

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85115095553&doi=10.1007%2f978-981-16-4486-3_14&partnerID=40&md5=3cf24f57d1e1d4d94666d9e3f7c7b09c