scholarly journals A Multi-Criteria Ranking Algorithm Based on the VIKOR Method for Meta-Search Engines

2019 ◽  
Vol 3 (3) ◽  
Author(s):  
Mojtaba Jamshidi ◽  
Mastoreh Haji ◽  
Mohamad Reza Kamankesh ◽  
Mahya Daghineh ◽  
Abdusalam Abdulla Shaltooki
Keyword(s):  
Search Engine ◽  
Search Engines ◽  
Access Time ◽  
Web Pages ◽  
Search Term ◽  
Ranking Algorithm ◽  
Vikor Method ◽  
Search Terms ◽  
Initial Dataset ◽  
Meta Search

Ranking of web pages is one of the most important parts of search engines and is, in fact, a process that through it the quality of a page is estimated by the search engine. In this study, a ranking algorithm based on VIKOR multi-criteria decision-making method for Meta-Search Engines (MSEs) was proposed. In this research, the considered MSE first will receive the suggested pages associated with the search term from eight search engines including, Teoma, Google, Yahoo!, AlltheWeb, AltaVista, Wisenut, ODP, MSN. The results, at most 10 first pages are selected from each search engine and creates the initial dataset contains 80 web pages. The proposed parser is then executed on these pages and the eight criteria including the rank of web page in the related search engine, access time, number of repetitions of search terms, positions of search term at the webpage, numbers of media at the webpage, the number of imports in the webpage, the number of incoming links, and the number of outgoing links are extracted from these web pages. Finally, by using the VIKOR method and these extracted criteria, web pages will rank and 10 top results will be provided for the user. To implement the proposed method, JAVA and MATLAB languages are used. In the experiments, the proposed method is implemented for a query and its ranking results have been compared in terms of accuracy with three famous search engine including Google, Yahoo, and MSN. The results of comparisons show that the proposed method offers higher accuracy.

Critical Analysis of Major Search Engines

2019 ◽  
Vol 16 (9) ◽  
pp. 3712-3716
Author(s):  
Kailash Kumar ◽  
Abdulaziz Al-Besher
Keyword(s):  
Search Engine ◽  
Search Engines ◽  
Critical Analysis ◽  
Research Paper ◽  
Web Pages ◽  
Ranking Algorithm ◽  
Sponsored Search ◽  
Web Page ◽  
Rigorous Analysis ◽  
The Common

This paper examines the overlapping of the results retrieved between three major search engines namely Google, Yahoo and Bing. A rigorous analysis of overlap among these search engines was conducted on 100 random queries. The overlap of first ten web page results, i.e., hundred results from each search engine and only non-sponsored results from these above major search engines were taken into consideration. Search engines have their own frequency of updates and ranking of results based on their relevance. Moreover, sponsored search advertisers are different for different search engines. Single search engine cannot index all Web pages. In this research paper, the overlapping analysis of the results were carried out between October 1, 2018 to October 31, 2018 among these major search engines namely, Google, Yahoo and Bing. A framework is built in Java to analyze the overlap among these search engines. This framework eliminates the common results and merges them in a unified list. It also uses the ranking algorithm to re-rank the search engine results and displays it back to the user.

scholarly journals Meta Search Engine using Semantic Similarity and Correlation Coefficient

2020 ◽  
Vol 9 (9) ◽  
pp. 643-647
Keyword(s):  
Search Engine ◽  
Search Engines ◽  
Search Space ◽  
The Other ◽  
Ranking Algorithm ◽  
Search Results ◽  
Ranking Algorithms ◽  
Meta Search Engine ◽  
User Query ◽  
Meta Search

This paper aims to provide an intelligent way to query and rank the results of a Meta Search Engine. A Meta Search Engine takes input from the user and produces results which are gathered from other search engines. The main advantage of a Meta Search Engine over methodical search engine is its ability to extend the search space and allows more resources for the user. The semantic intelligent queries will be fetching the results from different search engines and the responses will be fed into our ranking algorithm. Ranking of the search results is the other important aspect of Meta search engines. When a user searches a query, there are number of results retrieved from different search engines, but only several results are relevant to user's interest and others are not much relevant. Hence, it is important to rank results according to the relevancy with user query. The proposed paper uses intelligent query and ranking algorithms in order to provide intelligent meta search engine with semantic understanding.

scholarly journals An Ontology-based Ranking Model in Search Engines

2019 ◽  
Vol 1 (2) ◽  
Author(s):  
Yu Hou ◽  
Lixin Tao
Keyword(s):  
Search Engine ◽  
Search Engines ◽  
Semantic Search ◽  
The Internet ◽  
Web Pages ◽  
Ranking Algorithm ◽  
Intelligent Network ◽  
Web Page ◽  
Pagerank Algorithm ◽  
Hits Algorithm

As the tsunami of data has emerged, search engines have become the most powerful tool for obtaining scattered information on the internet. The traditional search engines return the organized results by using ranking algorithm such as term frequency, link analysis (PageRank algorithm and HITS algorithm) etc. However, these algorithms must combine the keyword frequency to determine the relevance between user’s query and the data in the computer system or internet. Moreover, we expect the search engines could understand users’ searching by content meanings rather than literal strings. Semantic Web is an intelligent network and it could understand human’s language more semantically and make the communication easier between human and computers. But, the current technology for the semantic search is hard to apply. Because some meta data should be annotated to each web pages, then the search engine will have the ability to understand the users intend. However, annotate every web page is very time-consuming and leads to inefficiency. So, this study designed an ontology-based approach to improve the current traditional keyword-based search and emulate the effects of semantic search. And let the search engine can understand users more semantically when it gets the knowledge.

A Review on Semantic Text and Multimedia Retrieval and Recent Trends

2015 ◽  
Vol 6 (1) ◽  
pp. 54-74
Author(s):  
Oğuzhan Menemencioğlu ◽  
İlhami Muharrem Orak
Keyword(s):  
Semantic Web ◽  
Search Engine ◽  
Search Engines ◽  
Semantic Search ◽  
Multimedia Retrieval ◽  
Web Pages ◽  
The Face ◽  
Recent Trends ◽  
New Applications ◽  
Machine Readable

Semantic web works on producing machine readable data and aims to deal with large amount of data. The most important tool to access the data which exist in web is the search engine. Traditional search engines are insufficient in the face of the amount of data that consists in the existing web pages. Semantic search engines are extensions to traditional engines and overcome the difficulties faced by them. This paper summarizes semantic web, concept of traditional and semantic search engines and infrastructure. Also semantic search approaches are detailed. A summary of the literature is provided by touching on the trends. In this respect, type of applications and the areas worked for are considered. Based on the data for two different years, trend on these points are analyzed and impacts of changes are discussed. It shows that evaluation on the semantic web continues and new applications and areas are also emerging. Multimedia retrieval is a newly scope of semantic. Hence, multimedia retrieval approaches are discussed. Text and multimedia retrieval is analyzed within semantic search.

scholarly journals Similarity Measurement Technique for Measuring the Performance of Page Rank Algorithm Based on Hadoop

2020 ◽  
Vol 8 (5) ◽  
pp. 4712-4717
Keyword(s):  
Big Data ◽  
Search Engine ◽  
Measurement Technique ◽  
Similarity Measurement ◽  
Web Pages ◽  
Ranking Algorithm ◽  
Web Data ◽  
Mapreduce Framework ◽  
Page Rank ◽  
Hadoop Mapreduce

In this century big data manipulation is a challenging task in the field of web mining because content of web data is massively increasing day by day. Using search engine retrieving efficient, relevant and meaningful information from massive amount of Web Data is quite impossible. Different search engine uses different ranking algorithm to retrieve relevant information easily. A new page ranking algorithm is presented based on synonymous word count using Hadoop MapReduce framework named as Similarity Measurement Technique (SMT). Hadoop MapReduce framework is used to partition Big Data and provides a scalable, economical and easier way to process these data. It stores intermediate result for running iterative jobs in the local disk. In this algorithm, SMT takes a query from user and parse it using Hadoop and calculate rank of web pages. For experimental purpose wiki data file have been used and applied page rank algorithm (PR), improvised page rank algorithm (IPR) and proposed SMT method to calculate page rank of all web pages and compare among these methods. Proposed method provides better scoring accuracy than other approaches and reduces theme drift problem.

scholarly journals Handling Complex Queries Using Query Trees

2021 ◽  
Author(s):  
Srihari Vemuru ◽  
Eric John ◽  
Shrisha Rao
Keyword(s):  
Search Engine ◽  
Search Engines ◽  
Knowledge Bases ◽  
Web Pages ◽  
Complex Query ◽  
Complex Queries ◽  
Tree Generation ◽  
Query Tree ◽  
Final Answer ◽  
Simple Query

Humans can easily parse and find answers to complex queries such as "What was the capital of the country of the discoverer of the element which has atomic number 1?" by breaking them up into small pieces, querying these appropriately, and assembling a final answer. However, contemporary search engines lack such capability and fail to handle even slightly complex queries. Search engines process queries by identifying keywords and searching against them in knowledge bases or indexed web pages. The results are, therefore, dependent on the keywords and how well the search engine handles them. In our work, we propose a three-step approach called parsing, tree generation, and querying (PTGQ) for effective searching of larger and more expressive queries of potentially unbounded complexity. PTGQ parses a complex query and constructs a query tree where each node represents a simple query. It then processes the complex query by recursively querying a back-end search engine, going over the corresponding query tree in postorder. Using PTGQ makes sure that the search engine always handles a simpler query containing very few keywords. Results demonstrate that PTGQ can handle queries of much higher complexity than standalone search engines.

scholarly journals Reliability of women epilepsy related information from main web search engines in China?deceitful web search environment and illumination (Preprint)

2017 ◽  
Author(s):  
Xi Zhu ◽  
Xiangmiao Qiu ◽  
Dingwang Wu ◽  
Shidong Chen ◽  
Jiwen Xiong ◽  
...  
Keyword(s):  
Search Engine ◽  
Search Engines ◽  
Web Search ◽  
Negative Impact ◽  
Academic Publishing ◽  
Web Pages ◽  
Efficient System ◽  
Related Information ◽  
Web Search Engines ◽  
Electronic Health

BACKGROUND All electronic health practices like app/software are involved in web search engine due to its convenience for receiving information. The success of electronic health has link with the success of web search engines in field of health. Yet information reliability from search engine results remains to be evaluated. A detail analysis can find out setbacks and bring inspiration. OBJECTIVE Find out reliability of women epilepsy related information from the searching results of main search engines in China. METHODS Six physicians conducted the search work every week. Search key words are one kind of AEDs (valproate acid/oxcarbazepine/levetiracetam/ lamotrigine) plus "huaiyun"/"renshen", both of which means pregnancy in Chinese. The search were conducted in different devices (computer/cellphone), different engines (Baidu/Sogou/360). Top ten results of every search result page were included. Two physicians classified every results into 9 categories according to their contents and also evaluated the reliability. RESULTS A total of 16411 searching results were included. 85.1% of web pages were with advertisement. 55% were categorized into question and answers according to their contents. Only 9% of the searching results are reliable, 50.7% are partly reliable, 40.3% unreliable. With the ranking of the searching results higher, advertisement up and the proportion of those unreliable increase. All contents from hospital websites are unreliable at all and all from academic publishing are reliable. CONCLUSIONS Several first principles must be emphasized to further the use of web search engines in field of healthcare. First, identification of registered physicians and development of an efficient system to guide the patients to physicians guarantee the quality of information provided. Second, corresponding department should restrict the excessive advertisement sale trades in healthcare area by specific regulations to avoid negative impact on patients. Third, information from hospital websites should be carefully judged before embracing them wholeheartedly.

scholarly journals WEB GRAPH BASED SEARCH BY USING DENSITY OF KEYWORD AND AGE FACTOR

2013 ◽  
pp. 89-93
Author(s):  
GAURAV AGARWAL ◽  
SACHI GUPTA ◽  
SAURABH MUKHERJEE
Keyword(s):  
Search Engine ◽  
Web Search ◽  
Web Pages ◽  
Main Role ◽  
Ranking Algorithm ◽  
Web Page ◽  
Web Crawler ◽  
User Requirement ◽  
Priority Assignment ◽  
The Web

Today, web servers, are the key repositories of the information & internet is the source of getting this information. There is a mammoth data on the Internet. It becomes a difficult job to search out the accordant data. Search Engine plays a vital role in searching the accordant data. A search engine follows these steps: Web crawling by crawler, Indexing by Indexer and Searching by Searcher. Web crawler retrieves information of the web pages by following every link on the site. Which is stored by web search engine then the content of the web page is indexed by the indexer. The main role of indexer is how data can be catch soon as per user requirements. As the client gives a query, Search Engine searches the results corresponding to this query to provide excellent output. Here ambition is to enroot an algorithm for search engine which may response most desirable result as per user requirement. In this a ranking method is used by the search engine to rank the web pages. Various ranking approaches are discussed in literature but in this paper, ranking algorithm is proposed which is based on parent-child relationship. Proposed ranking algorithm is based on priority assignment phase of Heterogeneous Earliest Finish Time (HEFT) Algorithm which is designed for multiprocessor task scheduling. Proposed algorithm works on three on range variable its means the density of keywords, number of successors to the nodes and the age of the web page. Density shows the occurrence of the keyword on the particular web page. Numbers of successors represent the outgoing link to a single web page. Age is the freshness value of the web page. The page which is modified recently is the freshest page and having the smallest age or largest freshness value. Proposed Technique requires that the priorities of each page to be set with the downward rank values & pages are arranged in ascending/ Descending order of their rank values. Experiments show that our algorithm is valuable. After the comparison with Google we find that our Algorithm is performing better. For 70% problems our algorithm is working better than Google.

scholarly journals Meta search engine

2021 ◽  
Author(s):  
Kwok-Pun Chan
Keyword(s):  
Foreign Language ◽  
Search Engine ◽  
Waiting Time ◽  
Search Engines ◽  
Time Frame ◽  
Search Result ◽  
Meta Search Engine ◽  
Meta Search ◽  
Biased Information

Meta search engines allow multiple engine searches to minimize biased information and improve the quality of the results it generates. However, existing meta engine applications contain many foreign language results, and only run on Windows platform. The meta search engine we develop will resolve these problems. Our search engine will run on both Windows and Linus platforms, and has some desirable properties: 1) users can shorten the search waiting time if one of the search engines is down 2) users can sort the result titles in an alphabetic or relevancy order. Current meta search websites only allow users to sort results by relevancy. Our search engine allows users to do an alphabetical search from the previous relevancy search result, so that the users can identify the required title within a shorter time frame.

scholarly journals Discovering How Students Search a Library Web Site: A Usability Case Study

2002 ◽  
Vol 63 (4) ◽  
pp. 354-365 ◽  
Author(s):  
Susan Augustine ◽  
Courtney Greene
Keyword(s):  
Search Engine ◽  
Long Range ◽  
Web Sites ◽  
Search Engines ◽  
Web Pages ◽  
Usability Study ◽  
Web Page ◽  
The Past ◽  
Library Resources

Have Internet search engines influenced the way students search library Web pages? The results of this usability study reveal that students consistently and frequently use the library Web site’s internal search engine to find information rather than navigating through pages. If students are searching rather than navigating, library Web page designers must make metadata and powerful search engines priorities. The study also shows that students have difficulty interpreting library terminology, experience confusion discerning difference amongst library resources, and prefer to seek human assistance when encountering problems online. These findings imply that library Web sites have not alleviated some of the basic and long-range problems that have challenged librarians in the past.

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