scholarly journals Effective Search Engine Spam Classification

2019 ◽  
Vol 8 (2S8) ◽  
pp. 1541-1545
Keyword(s):  
Decision Tree ◽  
Search Engine ◽  
Search Engines ◽  
Web Search ◽  
Web Pages ◽  
Classification Methods ◽  
Search Results ◽  
Web Search Engine ◽  
Engine Industry

Search engine spam is formed by the spam creators for commercial gain. Spammers applied different strategies in web pages to display the first page of web search results. These strategies may avoid displaying good quality web pages in the top of search engine results page. Nowadays there are numerous devised algorithms available to identify search engine spam. Even though search engines are still affected by search engine spam. There is a necessity for search engine industry to filter search engine spam in the best way. The proposed study identifies spam in web search engine. Spammers try to use most popular search keywords, popular links and advertising keywords in web pages. This strategy helps to increase ranking to display the top of search results. The proposed method is used important features to detect spam pages which are classified using decision tree C4.5 classifier. This method produces better performance when compared with existing classification methods.

Cluster Search Engine Results with Crowd Intelligence

2013 ◽  
Vol 284-287 ◽  
pp. 3375-3379
Author(s):  
Chun Hsiung Tseng ◽  
Fu Cheng Yang ◽  
Yu Ping Tseng ◽  
Yi Yun Chang
Keyword(s):  
Search Engine ◽  
Search Engines ◽  
Web Search ◽  
Web Pages ◽  
Huge Amount ◽  
Search Results ◽  
Web Search Engines ◽  
Crowd Intelligence ◽  
User Queries

Most Web users today rely heavily on search engines to gather information. To achieve better search results, some algorithms such as PageRank have been developed. However, most Web search engines employ keyword-based search and thus have some natural weaknesses. Among these problems, a well-known one is that it is very difficult for search engines to infer semantics from user queries and returned results. Hence, despite of efforts of ranking search results, users may still have to navigate through a huge amount of Web pages to locate the desired resources. In this research, the researchers developed a clustering-based methodology to improve the performance of search engines. Instead of extracting features used for clustering from the returned documents, the proposed method extracts features from the delicious service, which is actually a tag provider service. By utilizing such information, the resulting system can benefit from crowd intelligence. The obtained information is then used for enhancing the performance of the ordinary k-means algorithm to achieve better clustering results.

scholarly journals The Matter of Chance: Auditing Web Search Results Related to the 2020 U.S. Presidential Primary Elections Across Six Search Engines

2021 ◽  
pp. 089443932110068
Author(s):  
Aleksandra Urman ◽  
Mykola Makhortykh ◽  
Roberto Ulloa
Keyword(s):  
Search Engine ◽  
Search Engines ◽  
Large Scale ◽  
Web Search ◽  
Primary Elections ◽  
Virtual Agents ◽  
Search Results ◽  
Presidential Primary ◽  
Large Scale Analysis ◽  
Algorithmic Information

We examine how six search engines filter and rank information in relation to the queries on the U.S. 2020 presidential primary elections under the default—that is nonpersonalized—conditions. For that, we utilize an algorithmic auditing methodology that uses virtual agents to conduct large-scale analysis of algorithmic information curation in a controlled environment. Specifically, we look at the text search results for “us elections,” “donald trump,” “joe biden,” “bernie sanders” queries on Google, Baidu, Bing, DuckDuckGo, Yahoo, and Yandex, during the 2020 primaries. Our findings indicate substantial differences in the search results between search engines and multiple discrepancies within the results generated for different agents using the same search engine. It highlights that whether users see certain information is decided by chance due to the inherent randomization of search results. We also find that some search engines prioritize different categories of information sources with respect to specific candidates. These observations demonstrate that algorithmic curation of political information can create information inequalities between the search engine users even under nonpersonalized conditions. Such inequalities are particularly troubling considering that search results are highly trusted by the public and can shift the opinions of undecided voters as demonstrated by previous research.

Associating Searching on Search Engines to Subsequent Searching on Sites

2016 ◽  
Vol 8 (2) ◽  
pp. 30-43
Author(s):  
Adan Ortiz-Cordova ◽  
Bernard J. Jansen
Keyword(s):  
Search Engine ◽  
Search Engines ◽  
Web Search ◽  
Research Study ◽  
Search Queries ◽  
Web Search Engine ◽  
Search Patterns ◽  
Search Information

In this research study, the authors investigate the association between external searching, which is searching on a web search engine, and internal searching, which is searching on a website. They classify 295,571 external – internal searches where each search is composed of a search engine query that is submitted to a web search engine and then one or more subsequent queries submitted to a commercial website by the same user. The authors examine 891,453 queries from all searches, of which 295,571 were external search queries and 595,882 were internal search queries. They algorithmically classify all queries into states, and then clustered the searching episodes into major searching configurations and identify the most commonly occurring search patterns for both external, internal, and external-to-internal searching episodes. The research implications of this study are that external sessions and internal sessions must be considered as part of a continuous search episode and that online businesses can leverage external search information to more effectively target potential consumers.

Web Search Engine Architectures and their Performance Analysis

2011 ◽  
pp. 491-509
Author(s):  
Xiannong Meng
Keyword(s):  
Performance Analysis ◽  
Search Engine ◽  
Search Engines ◽  
Web Search ◽  
General Purpose ◽  
Performance Measurements ◽  
Web Documents ◽  
System Architectures ◽  
Web Search Engine ◽  
And Performance

This chapter surveys various technologies involved in a Web search engine with an emphasis on performance analysis issues. The aspects of a general-purpose search engine covered in this survey include system architectures, information retrieval theories as the basis of Web search, indexing and ranking of Web documents, relevance feedback and machine learning, personalization, and performance measurements. The objectives of the chapter are to review the theories and technologies pertaining to Web search, and help us understand how Web search engines work and how to use the search engines more effectively and efficiently.

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 Eysenbach, Tuische and Diepgen’s Evaluation of Web Searching for Identifying Unpublished Studies for Systematic Reviews: An Innovative Study Which is Still Relevant Today

2016 ◽  
Vol 11 (3) ◽  
pp. 108
Author(s):  
Simon Briscoe
Keyword(s):  
Systematic Review ◽  
Clinical Trials ◽  
Search Engine ◽  
Systematic Reviews ◽  
Search Engines ◽  
Web Search ◽  
Web Searching ◽  
Web Searches ◽  
Web Search Engine ◽  
Unpublished Studies

A Review of: Eysenbach, G., Tuische, J. & Diepgen, T.L. (2001). Evaluation of the usefulness of Internet searches to identify unpublished clinical trials for systematic reviews. Medical Informatics and the Internet in Medicine, 26(3), 203-218. http://dx.doi.org/10.1080/14639230110075459 Objective – To consider whether web searching is a useful method for identifying unpublished studies for inclusion in systematic reviews. Design – Retrospective web searches using the AltaVista search engine were conducted to identify unpublished studies – specifically, clinical trials – for systematic reviews which did not use a web search engine. Setting – The Department of Clinical Social Medicine, University of Heidelberg, Germany. Subjects – n/a Methods – Pilot testing of 11 web search engines was carried out to determine which could handle complex search queries. Pre-specified search requirements included the ability to handle Boolean and proximity operators, and truncation searching. A total of seven Cochrane systematic reviews were randomly selected from the Cochrane Library Issue 2, 1998, and their bibliographic database search strategies were adapted for the web search engine, AltaVista. Each adaptation combined search terms for the intervention, problem, and study type in the systematic review. Hints to planned, ongoing, or unpublished studies retrieved by the search engine, which were not cited in the systematic reviews, were followed up by visiting websites and contacting authors for further details when required. The authors of the systematic reviews were then contacted and asked to comment on the potential relevance of the identified studies. Main Results – Hints to 14 unpublished and potentially relevant studies, corresponding to 4 of the 7 randomly selected Cochrane systematic reviews, were identified. Out of the 14 studies, 2 were considered irrelevant to the corresponding systematic review by the systematic review authors. The relevance of a further three studies could not be clearly ascertained. This left nine studies which were considered relevant to a systematic review. In addition to this main finding, the pilot study to identify suitable search engines found that AltaVista was the only search engine able to handle the complex searches required to search for unpublished studies. Conclusion –Web searches using a search engine have the potential to identify studies for systematic reviews. Web search engines have considerable limitations which impede the identification of studies.

scholarly journals An investigation of biases in web search engine query suggestions

2019 ◽  
Vol 44 (2) ◽  
pp. 365-381 ◽  
Author(s):  
Malte Bonart ◽  
Anastasiia Samokhina ◽  
Gernot Heisenberg ◽  
Philipp Schaer
Keyword(s):  
Search Engine ◽  
Search Engines ◽  
Web Search ◽  
Query Suggestion ◽  
Data Set ◽  
Content Type ◽  
Web Search Engine ◽  
The Stability ◽  
Query Suggestions ◽  
Over Time

Purpose Survey-based studies suggest that search engines are trusted more than social media or even traditional news, although cases of false information or defamation are known. The purpose of this paper is to analyze query suggestion features of three search engines to see if these features introduce some bias into the query and search process that might compromise this trust. The authors test the approach on person-related search suggestions by querying the names of politicians from the German Bundestag before the German federal election of 2017. Design/methodology/approach This study introduces a framework to systematically examine and automatically analyze the varieties in different query suggestions for person names offered by major search engines. To test the framework, the authors collected data from the Google, Bing and DuckDuckGo query suggestion APIs over a period of four months for 629 different names of German politicians. The suggestions were clustered and statistically analyzed with regards to different biases, like gender, party or age and with regards to the stability of the suggestions over time. Findings By using the framework, the authors located three semantic clusters within the data set: suggestions related to politics and economics, location information and personal and other miscellaneous topics. Among other effects, the results of the analysis show a small bias in the form that male politicians receive slightly fewer suggestions on “personal and misc” topics. The stability analysis of the suggested terms over time shows that some suggestions are prevalent most of the time, while other suggestions fluctuate more often. Originality/value This study proposes a novel framework to automatically identify biases in web search engine query suggestions for person-related searches. Applying this framework on a set of person-related query suggestions shows first insights into the influence search engines can have on the query process of users that seek out information on politicians.

Design and Implementation of a Cache System in Web Search Engines

2013 ◽  
Vol 462-463 ◽  
pp. 1106-1109
Author(s):  
Hong Yuan Ma
Keyword(s):  
Search Engine ◽  
Search Engines ◽  
Web Search ◽  
Communication Architecture ◽  
Design And Implementation ◽  
Web Search Engine ◽  
Inverted List ◽  
Web Search Engines ◽  
Application Processor ◽  
Cache System

Web search engine caches the results which is frequently queried by users. It is an effective approach to improve the efficiency of Web search engines. In this paper, we give some valuable experience in our design and implementation of a Web search engine cache system. We present there design principles: logical layer processing, event-based communication architecture and avoiding frequent data copy. We also introduce the architecture presented in practice, including connection processor, application processor, query results caching processor, inverted list caching processor and list intersection caching processor. Experiments are conducted in our cache system using a real Web search engine query log.

A Study on Web Searching

2004 ◽  
pp. 208-225
Author(s):  
Shanfeng Zhu ◽  
Xiaotie Deng ◽  
Qizhi Fang ◽  
Weimin Zhang
Keyword(s):  
Search Engine ◽  
Search Engines ◽  
Web Search ◽  
Experimental Results ◽  
Web Searching ◽  
Search Results ◽  
Total Index ◽  
Depth Study ◽  
Web Search Engines ◽  
The Web

Web search engines are one of the most popular services to help users find useful information on the Web. Although many studies have been carried out to estimate the size and overlap of the general web search engines, it may not benefit the ordinary web searching users, since they care more about the overlap of the top N (N=10, 20 or 50) search results on concrete queries, but not the overlap of the total index database. In this study, we present experimental results on the comparison of the overlap of the top N (N=10, 20 or 50) search results from AlltheWeb, Google, AltaVista and WiseNut for the 58 most popular queries, as well as for the distance of the overlapped results. These 58 queries are chosen from WordTracker service, which records the most popular queries submitted to some famous metasearch engines, such as MetaCrawler and Dogpile. We divide these 58 queries into three categories for further investigation. Through in-depth study, we observe a number of interesting results: the overlap of the top N results retrieved by different search engines is very small; the search results of the queries in different categories behave in dramatically different ways; Google, on average, has the highest overlap among these four search engines; each search engine tends to adopt a different rank algorithm independently.

The Effects of Web Search Engine Query Ambiguity and Results Sorting Method on User Performance and Preference

2002 ◽  
Vol 46 (14) ◽  
pp. 1271-1275
Author(s):  
David N. Aurelio ◽  
Ronald R. Mourant
Keyword(s):  
Search Engine ◽  
Page Number ◽  
Web Search ◽  
User Performance ◽  
Query Term ◽  
Sorting Method ◽  
Search Results ◽  
Web Search Engine ◽  
Single Term ◽  
Insufficient Number

Users of Web search engines report two main problems: an insufficient number of relevant results and the mixing of relevant results with irrelevant results. Therefore, this research investigates the effects of query ambiguity and three forms of sorting search results on user performance and preference. Forty-eight Web search engine users evaluated three forms of sorting results. For each task, the query was a single term that had one, two, or three meanings. The results indicated that the preferred results sorting method was affected by the page number of the correct results. When the correct results were all located on the same page (i.e., the first page), the participants preferred the Ranking, Disambiguating, and Categories methods when the query term had one, two and three meanings, respectively. When the correct results were not on the first page, the test participants preferred the Categories sorting method for all number of query meanings.

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