Abstract. Scavenging Information Associated To Particular

This section discuss about the common traits or ideas observed in the three research topics. Although, each of the three articles discuss a unique idea, all of them are aimed at utilizing the web data to produce better results. Web data mining is a hot research topic in the current realm of big data. These papers discuss about the utilization of the valuable user generated data from the social media or the browser cookies to provide the best user experience in order to maintain the user interest in the company's product or to take effective decisions by an individual. All the three articles propose an idea to solution the problem stated, compared their results to the existing models and showed significant improvement.

Here we discuss about the common traits or ideas observed in the three research topics. Although, these three papers discuss about different ideas, they all fall under the web data mining domain. web data mining is a hot research topic in the current realm of big data. These papers discuss about the utilisation of the valuable user generated data from the social media or the the browser cookies to provide the best user experience in order to maintain the user interest in the company's product or to take effective decisions by the individual.

With the advent of computer technology in 1990’s the need to search large databases was increasingly becoming vital. The search engines prior to PageRank had limitations, the then most widely used algorithm used text based indexes to provide search results on World Wide Web however had limitations of improper search results as the logic used by the search engines looked at the number of occurrences of the search word in webpage which sometimes resulted in improper search results. Another technique used during the time was based on variations of standard vector space model – i.e. search based on how recent the webpage was updated and/or how close the search terms are to the

Q2: When you enter to AAU library system for search book titles about ' internet technology' as shown in the figure:

Launched on 15 January 2001, Wikipedia is a free encyclopedia that uses the web platform for online users to access. Boasting with over 26 million pieces of writing in 285 languages, Wikipedia has transformed to be a giant in the field of search engines optimization technology. The open source concept that it rides have made it cheap to access and a better choice for many online users. This is especially among the users who find it cumbersome to follow prolonged registration processes to access information on the internet. Any search term queried on the Google™ home page search engine will definitely give a hit from the Wikipedia site, and if not present, a prompt will request the user to create a page for such a term. In this way,

Programming testing is the methodology of executing a program or framework with the purpose of finding faults. Testing is a procedure of affirming that item is working as per the requirments, fulfilling the client needs. Programming testing gives a way to decrease errors, cut maintenance and general programming costs. Various programming testing strategies, techniques, and systems have developed in the course of the most recent couple of decades promising to improve programming quality. Programming testing is vital part in the product development life cycle. Two regular methodologies are white box testing and discovery testing. There are diverse scope measure for testability to the source code, for example, statement coverage, branch coverage and condition coverage. In the branch coverage we ensure that we execute each branch in any event once For conditional branches, this implies, we execute the TRUE branch in any event once and the FALSE branch in any event once conditions for conditional branches can be compound boolean expressions a compound boolean

(King-Lup Liu, 2001) Given countless motors on the Internet, it is troublesome for a man to figure out which web search tools could serve his/her data needs. A typical arrangement is to build a metasearch motor on top of the web indexes. After accepting a client question, the metasearch motor sends it to those fundamental web indexes which are liable to give back the craved archives for the inquiry. The determination calculation utilized by a metasearch motor to figure out if a web index ought to be sent the inquiry ordinarily settles on the choice in light of the web search tool agent, which contains trademark data about the database of a web search tool. Be that as it may, a hidden web index may not will to give the required data to the metasearch motor. This paper demonstrates that the required data can be evaluated from an uncooperative web crawler with great exactness. Two bits of data which license precise web crawler determination are the quantity of reports filed by the web index and the greatest weight of every term. In this paper, we display systems for the estimation of these two bits of data.

Final system suggests the predicted matches based on first hits stream data; this has been achieved by two step similarity functions, which built and developed similar incidents in web platform using Lucene and Clustering libraries. The K-means clustering and logistic regression methods has been trained to be used real-time to evaluate final safety scores categorized by labels, and provided label matching in particular safety concept group(s).

Following the success of Netscape and its web browser, Internet became a resource and communication platform idolized by many IT students in the universities. What started off as a hobby-cum-research[1] work by Jerry Yang (now Chief of Yahoo!) and David Filo (Co-founder of Yahoo!) for their Ph.D. dissertations; has evolved and became an Internet sensation over time. What they did was to compile all their favourite web links to form an online directory for easy navigation in the World Wide Web. The duo’s work immediately garnered a lot of attention from many surfers in the Internet world and before they realized it, Yahoo! became one of the most highly visited websites of all time. The duo saw the

Here, the revised non-dominated sorting genetic algorithm (NSGA-II), and non-dominated sorting differential evolution (NSDE) are detailed. The test system is given in section V, and simulation results are provided in section VI. Finally, conclusions are drawn and future research is suggested. II. MULTIOBJECTIVE OPTIMIZATION APPROACH

Made out of Web locales interconnected by hyperlinks, the World Wide Web can be seen as an enormous yet tumultuous wellspring of data. For choice making numerous business applications need to rely on upon web keeping in mind the end goal to total data from various sites. Programmed information extraction assumes an essential part in preparing results gave via internet searchers in the wake of presenting the question by client. presently days "site" has begun keeping more significance to our life. without which it is hard to oblige even one day .so it has turned into the need that the site ought to be more enlightening and alluring . be that as it may, the sites are created and just grew purposely or unwittingly

In the past ten years’ management of document grounded contents (together known as information retrieval – IR) have become very popular in the information systems field, due to the better availability of documents in digital form and subsequent necessity to access them in supple and effectual ways. Text categorization (TC), the movement of labeling natural language scripts with one or more types from a predefined set, is one such job. Machine learning (ML) methodology, according to which we can spontaneously build an automatic text classifier by learning, from a set of pre-classified text documents established on the characteristics of the categories of interest. The gains of this approach is accuracy as compared to that achieved by human beings, and an extensive savings in terms of expert manpower, since no involvement from either domain experts or knowledge engineers is required for the construction of the classifier.

All over the world, people through internet are connected and share their opinion. People are interested in official information as well as service and product that are available through online. To analyze different kinds of domain and aspect, online reviews, forums and blogs are used. Rapidly, internet become a dense network through which people not only access information but also interact with each other [1].

If we search for an answer to a question in a typical search engines such as Google, Bing, or Yahoo, it usually gives us relevant pages based on the key words in the query. We may need to follow several links or pages to reach a document providing a relevant answer. If we can store such search pathways to an answer for a given user query and reuse it for future searches it may speed up this process. Our question answering system motivated by reuse of prior web search pathways to yield an answer a user query. We represent queries and search pathways in a semi-structured format that contains query terms and referenced classes within a realm based ontology. First part of my research is to build a system that can automatically tag the terms in a user query to relevant classes from a domain-based ontology. The other part is to rank the prior searches (contains user queries, assigned classes, and search pathways) stored in the database based on the

The development of global networks is happening very rapidly. The number of Internet users in the world today is about 300 million people, and their number continues to grow. A new user registers to the Internet every two or three seconds. The number of web pages grows every day, and today there is more than a billion. Internet opens up a great opportunities for the distribution of information. You can find any interesting information online at any time, and then it can be easily copied to your hard drive. To truck the further use the copied material is very difficult. Subsequently, the same material can appear on another site – without specifying a name of an author, it can be in a distorted form, or both. And here arises a lot of