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.

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.

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.

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).

WEBCONTENT VISUALIZER: A VISUALIZATION SYSTEM FOR SEARCH ENGINES IN SEMATIC WEB

2011 ◽  
Vol 10 (05) ◽  
pp. 913-931 ◽  
Author(s):  
XIANYONG FANG ◽  
CHRISTIAN JACQUEMIN ◽  
FRÉDÉRIC VERNIER
Keyword(s):  
Semantic Web ◽  
Search Engine ◽  
Search Engines ◽  
Web Search ◽  
Search Query ◽  
Visualization System ◽  
Xml Documents ◽  
Web Search Engines ◽  
New Generation

Since the results from Semantic Web search engines are highly structured XML documents, they cannot be efficiently visualized with traditional explorers. Therefore, the Semantic Web calls for a new generation of search query visualizers that can rely on document metadata. This paper introduces such a visualization system called WebContent Visualizer that is used to display and browse search engine results. The visualization is organized into three levels: (1) Carousels contain documents with the same ranking, (2) carousels are piled into stacks, one for each date, and (3) these stacks are organized along a meta-carousel to display the results for several dates. Carousel stacks are piles of local carousels with increasing radii to visualize the ranks of classes. For document comparison, colored links connect documents between neighboring classes on the basis of shared entities. Based on these techniques, the interface is made of three collaborative components: an inspector window, a visualization panel, and a detailed dialog component. With this architecture, the system is intended to offer an efficient way to explore the results returned by Semantic Web search engines.

Rethinking gaming: The ethical work of optimization in web search engines

2019 ◽  
Vol 49 (5) ◽  
pp. 707-731 ◽  
Author(s):  
Malte Ziewitz
Keyword(s):  
Search Engine ◽  
Search Engines ◽  
Web Search ◽  
The United Kingdom ◽  
Ethical Work ◽  
Web Search Engines ◽  
The One ◽  
A Site ◽  
Shifting Boundaries ◽  
Precarious Situation

When measures come to matter, those measured find themselves in a precarious situation. On the one hand, they have a strong incentive to respond to measurement so as to score a favourable rating. On the other hand, too much of an adjustment runs the risk of being flagged and penalized by system operators as an attempt to ‘game the system’. Measures, the story goes, are most useful when they depict those measured as they usually are and not how they intend to be. In this article, I explore the practices and politics of optimization in the case of web search engines. Drawing on materials from ethnographic fieldwork with search engine optimization (SEO) consultants in the United Kingdom, I show how maximizing a website’s visibility in search results involves navigating the shifting boundaries between ‘good’ and ‘bad’ optimization. Specifically, I am interested in the ethical work performed as SEO consultants artfully arrange themselves to cope with moral ambiguities provoked and delegated by the operators of the search engine. Building on studies of ethics as a practical accomplishment, I suggest that the ethicality of optimization has itself become a site of governance and contestation. Studying such practices of ‘being ethical’ not only offers opportunities for rethinking popular tropes like ‘gaming the system’, but also draws attention to often-overlooked struggles for authority at the margins of contemporary ranking schemes.

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.

Perspectives and Key Technologies of Semantic Web Search

2011 ◽  
pp. 1532-1537 ◽  
Author(s):  
Konstantinos Kotis
Keyword(s):  
Semantic Web ◽  
Search Engines ◽  
Web Search ◽  
Semantic Search ◽  
Web Pages ◽  
Domain Specific ◽  
Web Information ◽  
Natural Language Query ◽  
Web Search Engines ◽  
Semantically Heterogeneous

Current keyword-based Web search engines (e.g. Googlea) provide access to thousands of people for billions of indexed Web pages. Although the amount of irrelevant results returned due to polysemy (one word with several meanings) and synonymy (several words with one meaning) linguistic phenomena tends to be reduced (e.g. by narrowing the search using human- directed topic hierarchies as in Yahoob), still the uncontrolled publication of Web pages requires an alternative to the way Web information is authored and retrieved today. This alternative can be the technologies of the new era of the Semantic Web. The Semantic Web, currently using OWL language to describe content, is an extension and an alternative at the same time to the traditional Web. A Semantic Web Document (SWD) describes its content with semantics, i.e. domain-specific tags related to a specific conceptualization of a domain, adding meaning to the document’s (annotated) content. Ontologies play a key role to providing such description since they provide a standard way for explicit and formal conceptualizations of domains. Since traditional Web search engines cannot easily take advantage of documents’ semantics, e.g. they cannot find documents that describe similar concepts and not just similar words, semantic search engines (e.g. SWOOGLEc, OntoSearchd) and several other semantic search technologies have been proposed (e.g. Semantic Portals (Zhang et al, 2005), Semantic Wikis (Völkel et al, 2006), multi-agent P2P ontology-based semantic routing (of queries) systems (Tamma et al, 2004), and ontology mapping-based query/answering systems (Lopez et al, 2006; Kotis & Vouros, 2006, Bouquet et al, 2004). Within these technologies, queries can be placed as formally described (or annotated) content, and a semantic matching algorithm can provide the exact matching with SWDs that their semantics match the semantics of the query. Although the Semantic Web technology contributes much in the retrieval of Web information, there are some open issues to be tackled. First of all, unstructured (traditional Web) documents must be semantically annotated with domain-specific tags (ontology-based annotation) in order to be utilized by semantic search technologies. This is not an easy task, and requires specific domain ontologies to be developed that will provide such semantics (tags). A fully automatic annotation process is still an open issue. On the other hand, SWDs can be semantically retrieved only by formal queries. The construction of a formal query is also a difficult and time-consuming task since a formal language must be learned. Techniques towards automating the transformation of a natural language query to a formal (structured) one are currently investigated. Nevertheless, more sophisticated technologies such as the mapping of several schemes to a formal query constructed in the form of an ontology must be investigated. The technology is proposed for retrieving heterogeneous and distributed SWDs, since their structure cannot be known a priory (in open environments like the Semantic Web). This article aims to provide an insight on current technologies used in Semantic Web search, focusing on two issues: a) the automatic construction of a formal query (query ontology) and b) the querying of a collection of knowledge sources whose structure is not known a priory (distributed and semantically heterogeneous documents).

TemporalClassifier

2018 ◽  
pp. 1143-1165
Author(s):  
Rahul Pradhan ◽  
Dilip Kumar Sharma
Keyword(s):  
Search Engine ◽  
Search Engines ◽  
Web Search ◽  
Web Page ◽  
Temporal Expression ◽  
Course Of Action ◽  
Temporal Boundary ◽  
Web Search Engines ◽  
The Web

Users issuing query on search engine, expect results to more relevant to query topic rather than just the textual match with text in query. Studies conducted by few researchers shows that user want the search engine to understand the implicit intent of query rather than looking the textual match in hypertext structure of document or web page. In this paper the authors will be addressing queries that have any temporal intent and help the web search engines to classify them in certain categories. These classes or categories will help search engine to understand and cater the need of query. The authors will consider temporal expression (e.g. 1943) in document and categories them on the basis of temporal boundary of that query. Their experiment classifies the query and tries to suggest further course of action for search engines. Results shows that classifying the query to these classes will help user to reach his/her seeking information faster.

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.

A Semantic-Based Dynamic Search Engine Design and Implementation for Electronic Medical Records

2012 ◽  
pp. 285-297
Author(s):  
Weider D. Yu ◽  
Seshadri K. Yilayavilli
Keyword(s):  
Search Engine ◽  
Search Engines ◽  
First Generation ◽  
Web Search ◽  
Relevant Information ◽  
Engine Design ◽  
Search Service ◽  
Web Search Engines ◽  
World Information ◽  
The Right

In the current technology driven world, information retrieval activities are in almost every aspect of daily, as society uses popular web search engines like Google, Yahoo!, Live Search, Ask, and so forth to obtain helpful information. Often, these popular search engines look for and obtain key information; however, not all of the retrieved items are relevant in context to the search target a. Thus, it is left for the user to filter out unwanted information, using only a few information items left from the search results. These popular web search engines use a first generation search service based on “static keywords”, which require the users to know exactly what they want to search and enter the right keywords. This approach puts the user at a disadvantage. In this paper, the authors investigate and design a dynamic, question-answer search engine that enables searching by attributes for more precise and relevant information in Electronic Medical Record (EMR) field.

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