Implementation of Web Application for Disease Prediction Using AI

The Internet is the largest source of information created by humanity. It contains a variety of materials available in various formats such as text, audio, video and much more. In all web scraping is one way. It is a set of strategies here in which we get information from the website instead of copying the data manually. Many Web-based data extraction methods are designed to solve specific problems and work on ad-hoc domains. Various tools and technologies have been developed to facilitate Web Scraping. Unfortunately, the appropriateness and ethics of using these Web Scraping tools are often overlooked. There are hundreds of web scraping software available today, most of them designed for Java, Python and Ruby. There is also open source software and commercial software. Web-based software such as YahooPipes, Google Web Scrapers and Firefox extensions for Outwit are the best tools for beginners in web cutting. Web extraction is basically used to cut this manual extraction and editing process and provide an easy and better way to collect data from a web page and convert it into the desired format and save it to a local or archive directory. In this paper, among others the kind of scrub, we focus on those techniques that extract the content of a Web page. In particular, we use scrubbing techniques for a variety of diseases with their own symptoms and precautions.

Improving Performance of DOM in Semi-structured Data Extraction using WEIDJ Model

<p>Web data extraction is the process of extracting user required information from web page. The information consists of semi-structured data not in structured format. The extraction data involves the web documents in html format. Nowadays, most people uses web data extractors because the extraction involve large information which makes the process of manual information extraction takes time and complicated. We present in this paper WEIDJ approach to extract images from the web, whose goal is to harvest images as object from template-based html pages. The WEIDJ (Web Extraction Image using DOM (Document Object Model) and JSON (JavaScript Object Notation)) applies DOM theory in order to build the structure and JSON as environment of programming. The extraction process leverages both the input of web address and the structure of extraction. Then, WEIDJ splits DOM tree into small subtrees and applies searching algorithm by visual blocks for each web page to find images. Our approach focus on three level of extraction; single web page, multiple web page and the whole web page. Extensive experiments on several biodiversity web pages has been done to show the comparison time performance between image extraction using DOM, JSON and WEIDJ for single web page. The experimental results advocate via our model, WEIDJ image extraction can be done fast and effectively.</p>

Optimal Query Generation for Hidden Web Extraction Through Response Analysis

A huge number of Hidden Web databases exists over the WWW forming a massive source of high quality information. Retrieval of this information for enriching the repository of the search engine is the prime target of a Hidden web crawler. Besides this, the crawler should perform this task at an affordable cost and resource utilization. This paper proposes a Random ranking mechanism whereby the queries to be raised by the hidden web crawler have been ranked. By ranking the queries according to the proposed mechanism, the Hidden Web crawler is able to make an optimal choice among the candidate queries and efficiently retrieve the Hidden web databases. The Hidden Web crawler proposed here also possesses an extensible and scalable framework to improve the efficiency of crawling. The proposed approach has also been compared with other methods of Hidden Web crawling existing in the literature.

Design and Implementation of Web Extraction System of Ceramic Products’ Information in the Business Website

In the means of getting information from the Internet, the Web information extraction technology which can get more precise and more granular information is different from Search Engine, this article presents the technical route of Web information exaction of ceramic products’ information on the basis of analyzing the developing status of Web information extraction technology at home and abroad, and makes the extraction rules, and develops a set of extraction system, and acquires the relevant ceramic products’ information.

Optimal Query Generation for Hidden Web Extraction through Response Analysis

A huge number of Hidden Web databases exists over the WWW forming a massive source of high quality information. Retrieval of this information for enriching the repository of the search engine is the prime target of a Hidden web crawler. Besides this, the crawler should perform this task at an affordable cost and resource utilization. This paper proposes a Random ranking mechanism whereby the queries to be raised by the hidden web crawler have been ranked. By ranking the queries according to the proposed mechanism, the Hidden Web crawler is able to make an optimal choice among the candidate queries and efficiently retrieve the Hidden web databases. The Hidden Web crawler proposed here also possesses an extensible and scalable framework to improve the efficiency of crawling. The proposed approach has also been compared with other methods of Hidden Web crawling existing in the literature.

Process Model for Content Extraction from Weblogs

This paper develops and evaluates a BPMN-based process model which identifies and extracts blog content from the web and stores its textual data in a data warehouse for further analyses. Depending on the characteristics of the technologies used to create the weblogs, the process has to perform specific tasks in order to extract blog content correctly. The paper describes three phases: extraction, transformation and loading of data in a repository specifically adapted for blog content extraction. It highlights the objectives in these phases which must be achieved to ensure the correct extraction. The authors integrate the described process in a previously developed framework for blog mining. The authors' process model closes the conceptual gap in this framework as well as the gap in current research of blog mining process models. Furthermore, it can easily be adapted for other web extraction proposals.