Converging Cellular Automata Techniques with Web Search Methods to Offer a New Way to Rank Hyper-linked Web-Pages

2007 ◽  
Author(s):  
Anirban Kundu ◽  
Ruma Dutta ◽  
Debajyoti Mukhopadhyay
Keyword(s):  
Cellular Automata ◽  
Web Search ◽  
Web Pages ◽  
Search Methods

Classification of Spamming Attacks to Blogging Websites and Their Security Techniques

2020 ◽  
pp. 864-880 ◽  
Author(s):  
Rizwan Ur Rahman ◽  
Rishu Verma ◽  
Himani Bansal ◽  
Deepak Singh Tomar
Keyword(s):  
Search Engine ◽  
World Wide ◽  
Web Search ◽  
Service Providers ◽  
Web Pages ◽  
Internet Service ◽  
Important Concern ◽  
Attack Scenario ◽  
Explosive Expansion

With the explosive expansion of information on the world wide web, search engines are becoming more significant in the day-to-day lives of humans. Even though a search engine generally gives huge number of results for certain query, the majority of the search engine users simply view the first few web pages in result lists. Consequently, the ranking position has become a most important concern of internet service providers. This article addresses the vulnerabilities, spamming attacks, and countermeasures in blogging sites. In the first part, the article explores the spamming types and detailed section on vulnerabilities. In the next part, an attack scenario of form spamming is presented, and defense approach is presented. Consequently, the aim of this article is to provide review of vulnerabilities, threats of spamming associated with blogging websites, and effective measures to counter them.

Search Engine

The Dark Web ◽  
2018 ◽  
pp. 359-374
Author(s):  
Dilip Kumar Sharma ◽  
A. K. Sharma
Keyword(s):  
Computer Networks ◽  
Search Engines ◽  
Web Search ◽  
Relevant Information ◽  
Vital Role ◽  
Deep Web ◽  
Telecommunication Networks ◽  
Web Pages ◽  
Web Crawler ◽  
Main Components

ICT plays a vital role in human development through information extraction and includes computer networks and telecommunication networks. One of the important modules of ICT is computer networks, which are the backbone of the World Wide Web (WWW). Search engines are computer programs that browse and extract information from the WWW in a systematic and automatic manner. This paper examines the three main components of search engines: Extractor, a web crawler which starts with a URL; Analyzer, an indexer that processes words on the web page and stores the resulting index in a database; and Interface Generator, a query handler that understands the need and preferences of the user. This paper concentrates on the information available on the surface web through general web pages and the hidden information behind the query interface, called deep web. This paper emphasizes the Extraction of relevant information to generate the preferred content for the user as the first result of his or her search query. This paper discusses the aspect of deep web with analysis of a few existing deep web search engines.

Enhancing Web Search through Query Expansion

2011 ◽  
pp. 752-757 ◽  
Author(s):  
Daniel Crabtree
Keyword(s):  
Information Retrieval ◽  
Search Engines ◽  
Query Expansion ◽  
Web Search ◽  
User Involvement ◽  
Semantic Knowledge ◽  
Web Pages ◽  
Search Performance ◽  
Interactive Query ◽  
Web Search Engines

Web search engines help users find relevant web pages by returning a result set containing the pages that best match the user’s query. When the identified pages have low relevance, the query must be refined to capture the search goal more effectively. However, finding appropriate refinement terms is difficult and time consuming for users, so researchers developed query expansion approaches to identify refinement terms automatically. There are two broad approaches to query expansion, automatic query expansion (AQE) and interactive query expansion (IQE) (Ruthven et al., 2003). AQE has no user involvement, which is simpler for the user, but limits its performance. IQE has user involvement, which is more complex for the user, but means it can tackle more problems such as ambiguous queries. Searches fail by finding too many irrelevant pages (low precision) or by finding too few relevant pages (low recall). AQE has a long history in the field of information retrieval, where the focus has been on improving recall (Velez et al., 1997). Unfortunately, AQE often decreased precision as the terms used to expand a query often changed the query’s meaning (Croft and Harper (1979) identified this effect and named it query drift). The problem is that users typically consider just the first few results (Jansen et al., 2005), which makes precision vital to web search performance. In contrast, IQE has historically balanced precision and recall, leading to an earlier uptake within web search. However, like AQE, the precision of IQE approaches needs improvement. Most recently, approaches have started to improve precision by incorporating semantic knowledge.

Search Engine

2011 ◽  
Vol 3 (2) ◽  
pp. 38-51 ◽  
Author(s):  
Dilip Kumar Sharma ◽  
A. K. Sharma
Keyword(s):  
Computer Networks ◽  
Search Engines ◽  
Web Search ◽  
Relevant Information ◽  
Vital Role ◽  
Deep Web ◽  
Telecommunication Networks ◽  
Web Pages ◽  
Web Crawler ◽  
Main Components

ICT plays a vital role in human development through information extraction and includes computer networks and telecommunication networks. One of the important modules of ICT is computer networks, which are the backbone of the World Wide Web (WWW). Search engines are computer programs that browse and extract information from the WWW in a systematic and automatic manner. This paper examines the three main components of search engines: Extractor, a web crawler which starts with a URL; Analyzer, an indexer that processes words on the web page and stores the resulting index in a database; and Interface Generator, a query handler that understands the need and preferences of the user. This paper concentrates on the information available on the surface web through general web pages and the hidden information behind the query interface, called deep web. This paper emphasizes the Extraction of relevant information to generate the preferred content for the user as the first result of his or her search query. This paper discusses the aspect of deep web with analysis of a few existing deep web search engines.

An Intelligent Web Search Using Multi-Document Summarization

2016 ◽  
Vol 6 (2) ◽  
pp. 41-65 ◽  
Author(s):  
Sheetal A. Takale ◽  
Prakash J. Kulkarni ◽  
Sahil K. Shah
Keyword(s):  
Search Engine ◽  
Web Search ◽  
Document Clustering ◽  
The Internet ◽  
Web Pages ◽  
Extractive Summarization ◽  
Text Understanding ◽  
User Query ◽  
Sentence Clustering

Information available on the internet is huge, diverse and dynamic. Current Search Engine is doing the task of intelligent help to the users of the internet. For a query, it provides a listing of best matching or relevant web pages. However, information for the query is often spread across multiple pages which are returned by the search engine. This degrades the quality of search results. So, the search engines are drowning in information, but starving for knowledge. Here, we present a query focused extractive summarization of search engine results. We propose a two level summarization process: identification of relevant theme clusters, and selection of top ranking sentences to form summarized result for user query. A new approach to semantic similarity computation using semantic roles and semantic meaning is proposed. Document clustering is effectively achieved by application of MDL principle and sentence clustering and ranking is done by using SNMF. Experiments conducted demonstrate the effectiveness of system in semantic text understanding, document clustering and summarization.

AntWeb—Web Search Based on Ant Behavior

2008 ◽  
pp. 208-222
Author(s):  
Li Weigang ◽  
Wu Man Qi
Keyword(s):  
Web Mining ◽  
Web Search ◽  
Theory Model ◽  
Web Pages ◽  
Web Portal ◽  
Knowledge Based ◽  
Log Files ◽  
Ant Behavior ◽  
Shortest Route ◽  
The Web

This chapter presents a study of Ant Colony Optimization (ACO) to Interlegis Web portal, Brazilian legislation Website. The approach of AntWeb is inspired by ant colonies foraging behavior to adaptively mark the most significant link by means of the shortest route to arrive the target pages. The system considers the users in the Web portal as artificial ants and the links among the pages of the Web pages as the researching network. To identify the group of the visitors, Web mining is applied to extract knowledge based on preprocessing Web log files. The chapter describes the theory, model, main utilities and implementation of AntWeb prototype in Interlegis Web portal. The case study shows Off-line Web mining; simulations without and with the use of AntWeb; testing by modification of the parameters. The result demonstrates the sensibility and accessibility of AntWeb and the benefits for the Interlegis Web users.

A Web Metadata Based-Model for Information Quality Prediction

2011 ◽  
pp. 324-343 ◽  
Author(s):  
Ricardo Barros ◽  
Geraldo Xexéo ◽  
Wallace A. Pinheiro ◽  
Jano de Souza
Keyword(s):  
Information Quality ◽  
Web Search ◽  
Fuzzy Theory ◽  
Web Pages ◽  
Quality Prediction ◽  
Theory Approach ◽  
Web Environment ◽  
Conflicting Information ◽  
Quality Dimensions

Currently, in the Web environment, users have to deal with an enormous amount of information. In a Web search, they often receive useless, replicated, outdated, or false data, which, at first, they have no means to assess. Web search engines provide good examples of these problems: As reply from these mechanisms, users usually find links to replicated or conflicting information. Further, in these cases, information is spread out among heterogeneous and unrelated data sources, that normally present different information quality approaches. This chapter addresses those issues by proposing a Web Metadata-Based Model to evaluate and recommend Web pages based on their information quality, as predicted by their metadata. We adopt a fuzzy theory approach to obtain the values of quality dimensions from metadata values and to evaluate the quality of information, taking advantage of fuzzy logic’s ability to capture humans’ imprecise knowledge and deal with different concepts.

Enhancing Web Search through Web Structure Mining

2011 ◽  
pp. 443-447
Author(s):  
Ji-Rong Wen
Keyword(s):  
Information Retrieval ◽  
Web Search ◽  
Product Information ◽  
Semantic Representation ◽  
Web Pages ◽  
Search Performance ◽  
Information Display ◽  
Web Structure Mining ◽  
Free Environment ◽  
The Web

The Web is an open and free environment for people to publish and get information. Everyone on the Web can be either an author, a reader, or both. The language of the Web, HTML (Hypertext Markup Language), is mainly designed for information display, not for semantic representation. Therefore, current Web search engines usually treat Web pages as unstructured documents, and traditional information retrieval (IR) technologies are employed for Web page parsing, indexing, and searching. The unstructured essence of Web pages seriously blocks more accurate search and advanced applications on the Web. For example, many sites contain structured information about various products. Extracting and integrating product information from multiple Web sites could lead to powerful search functions, such as comparison shopping and business intelligence. However, these structured data are embedded in Web pages, and there are no proper traditional methods to extract and integrate them. Another example is the link structure of the Web. If used properly, information hidden in the links could be taken advantage of to effectively improve search performance and make Web search go beyond traditional information retrieval (Page, Brin, Motwani, & Winograd, 1998, Kleinberg, 1998).

World Wide Web Search Technologies

2005 ◽  
pp. 3111-3117
Author(s):  
Wen-Chen Hu ◽  
Hung-Jen Yang ◽  
Jyh-haw Yeh ◽  
Chung-wei Lee
Keyword(s):  
Information Retrieval ◽  
World Wide Web ◽  
Search Engines ◽  
World Wide ◽  
Web Search ◽  
Future Research ◽  
Web Pages ◽  
Future Research Directions ◽  
Web Search Engines ◽  
Almost All

The World Wide Web now holds more than six billion pages covering almost all daily issues. The Web’s fast growing size and lack of structural style present a new challenge for information retrieval (Lawrence & Giles, 1999a). Traditional search techniques are based on users typing in search keywords which the search services can then use to locate the desired Web pages. However, this approach normally retrieves too many documents, of which only a small fraction are relevant to the users’ needs. Furthermore, the most relevant documents do not necessarily appear at the top of the query output list. Numerous search technologies have been applied to Web search engines; however, the dominant search methods have yet to be identified. This article provides an overview of the existing technologies for Web search engines and classifies them into six categories: i) hyperlink exploration, ii) information retrieval, iii) metasearches, iv) SQL approaches, v) content-based multimedia searches, and vi) others. At the end of this article, a comparative study of major commercial and experimental search engines is presented, and some future research directions for Web search engines are suggested. Related Web search technology review can also be found in Arasu, Cho, Garcia-Molina, Paepcke, and Raghavan (2001) and Lawrence and Giles (1999b).

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