scholarly journals LaneConnex: An Integrated Biomedical Digital Library Interface

2009 ◽  
Vol 28 (1) ◽  
pp. 31
Author(s):  
Debra S. Ketchell ◽  
Ryan Max Steinberg ◽  
Charles Yates ◽  
Heidi A. Heilemann
Keyword(s):  
User Interface ◽  
Digital Library ◽  
Full Text ◽  
Search Engines ◽  
Web Search ◽  
Search Interface ◽  
Institutional Investment ◽  
Content Type ◽  
Bioinformatics Tools ◽  
Simple Query

<span>This paper describes one approach to creating a search application that unlocks heterogeneous content stores and incorporates integrative functionality of Web search engines. LaneConnex is a search interface that identifies journals, books, databases, calculators, bioinformatics tools, help information, and search hits from more than three hundred full-text heterogeneous clinical and bioresearch sources. The user interface is a simple query box. Results are ranked by relevance with options for filtering by content type or expanding to the next most likely set. The system is built using component-oriented programming design. The underlying architecture is built on Apache Cocoon, Java Servlets, XML/XSLT, SQL, and JavaScript. The system has proven reliable in production, reduced user time spent finding information on the site, and maximized the institutional investment in licensed resources.</span>

The trained and untrained users’ mental models compatibility with the icons of search modules in Iranian digital library applications

2017 ◽  
Vol 35 (2) ◽  
pp. 290-302 ◽  
Author(s):  
Sanaz Rahrovani ◽  
Mahdieh Mirzabeigi ◽  
Javad Abbaspour
Keyword(s):  
User Interface ◽  
Mental Models ◽  
Information Literacy ◽  
Digital Library ◽  
Design Methodology ◽  
User Group ◽  
Content Type ◽  
Software Applications ◽  
Fields Of Study ◽  
Study Results

Purpose The purpose of this paper is to investigate the trained and untrained users’ mental models compatibility with search module icons in three Iranian digital library applications, namely, Nika, Azarakhsh, and Simorgh. Design/methodology/approach The population of this survey consisted of two groups including trained and untrained users. The trained user group consisted of 174 samples, all of which were included in the study due to scarcity of the samples. The untrained user group consisted of 8,210 samples, from which 267 cases were selected through stratified sampling. Findings Results showed that the trained users’ mental models were more compatible with the search module icons than those of the untrained users. The comparison of three software applications showed that the mental models of trained and untrained users had the highest compatibility with the search icons of Azarakhsh and the lowest compatibility with those of Nika. Concerning the untrained users’ status in terms of their fields of study, results showed that users majoring technical and engineering field and those in agriculture had, respectively, the highest and lowest mental models compatibility with the icons embedded in the user interface of the studied applications. Originality/value Since the mental models may be incomplete or inaccurate, the study of the trained and untrained users’ mental models compatibility with the search module icons of user interface embedded in various library applications may help in assessing the software’ status and the designers’ level of success in conveying the content. This also may assist information literacy specialists to estimate the required amount of training for trained and untrained users.

Evaluating search features of Google Knowledge Graph and Bing Satori

2015 ◽  
Vol 39 (2) ◽  
pp. 197-213 ◽  
Author(s):  
Ahmet Uyar ◽  
Farouk Musa Aliyu
Keyword(s):  
Semantic Web ◽  
Natural Language ◽  
Search Engines ◽  
Web Search ◽  
Semantic Search ◽  
Knowledge Graph ◽  
Content Type ◽  
Query Interfaces ◽  
Natural Language Query ◽  
Web Search Engines

Purpose – The purpose of this paper is to better understand three main aspects of semantic web search engines of Google Knowledge Graph and Bing Satori. The authors investigated: coverage of entity types, the extent of their support for list search services and the capabilities of their natural language query interfaces. Design/methodology/approach – The authors manually submitted selected queries to these two semantic web search engines and evaluated the returned results. To test the coverage of entity types, the authors selected the entity types from Freebase database. To test the capabilities of natural language query interfaces, the authors used a manually developed query data set about US geography. Findings – The results indicate that both semantic search engines cover only the very common entity types. In addition, the list search service is provided for a small percentage of entity types. Moreover, both search engines support queries with very limited complexity and with limited set of recognised terms. Research limitations/implications – Both companies are continually working to improve their semantic web search engines. Therefore, the findings show their capabilities at the time of conducting this research. Practical implications – The results show that in the near future the authors can expect both semantic search engines to expand their entity databases and improve their natural language interfaces. Originality/value – As far as the authors know, this is the first study evaluating any aspect of newly developing semantic web search engines. It shows the current capabilities and limitations of these semantic web search engines. It provides directions to researchers by pointing out the main problems for semantic web search engines.

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.

Using a digital library instead of a traditional database

2015 ◽  
Vol 33 (5) ◽  
pp. 916-927 ◽  
Author(s):  
Michael Trachtengerts ◽  
Adilbek Erkimbaev ◽  
Vladimir Zitserman ◽  
Georgii Kobzev
Keyword(s):  
Information Systems ◽  
Digital Library ◽  
Digital Libraries ◽  
Full Text ◽  
Design Methodology ◽  
Modern Science ◽  
Content Type ◽  
External Sources ◽  
The Subject ◽  
Functional Capacities

Purpose – The purpose of this paper is to reveal main advantages of digital libraries in comparison with technology of common database for data-oriented fields of modern science. As an example, the subject domain “nanomaterials and nanotechnologies” with new features due to evolution of concepts and objects is presented. Design/methodology/approach – An analysis of the information system ABCD as a basis for science-oriented digital library was fulfilled. Also, a survey of peculiarities of data in fast developing fields of science was prepared. Findings – The results of this paper showed that functional capacities of ABCD satisfy requirements for complex collections and archives of scientific documents. Based on the ABCD tools and this concept, the digital library for storage and systematization of data and documents on nanomaterials and nanotechnologies for the power engineering was constructed. The library combines opportunities of bibliographic, full text and factual information systems. Originality/value – This paper gives the foundation for creation of a library that combines services of bibliographic, full text and factual (numerical) information systems. Some analyses of ABCD tools were made before elsewhere, but they did not point on data peculiarities of complexly organized domains: semi-structured data, multitude formats (text, image and tables), interconnection of content with external sources located on other servers or in the Web.

Using data island method for creating metadata records with indexability and visibility of tag names in web search engines

2014 ◽  
Vol 32 (1) ◽  
pp. 83-97 ◽  
Author(s):  
Sayyed Mahdi Taheri ◽  
Nadjla Hariri ◽  
Sayyed Rahmatollah Fattahi
Keyword(s):  
Search Engines ◽  
Web Search ◽  
Normal Structure ◽  
Control Group ◽  
Content Type ◽  
Indexing And Retrieval ◽  
Web Search Engines ◽  
Using Data ◽  
First Time ◽  
Experimental Group

Purpose – The aim of this research was to examine the use of the data island method for creating metadata records based on DCXML, MARCXML, and MODS with indexability and visibility of element tag names in web search engines. Design/methodology/approach – A total of 600 metadata records were developed in two groups (300 HTML-based records in an experimental group with special structure embedded in the < pre> tag of HTML based on the data island method, and 300 XML-based records as the control group with the normal structure). These records were analyzed through an experimental approach. The records of these two groups were published on two independent websites, and were submitted to Google and Bing search engines. Findings – Findings show that all the tag names of the metadata records created based on the data island method relating to the experimental group indexed by Google and Bing were visible in the search results. But the tag names in the control group's metadata records were not indexed by the search engines. Accordingly it is possible to index and retrieve the metadata records by their tag name in the search engines. But the records of the control group are accessible by the element values only. The research suggests some patterns to the metadata creators and the end users for better indexing and retrieval. Originality/value – The research used the data island method for creating the metadata records, and deals with the indexability and visibility of the metadata element tag names for the first time.

scholarly journals “Outside the industry, nobody knows what we do” SEO as seen by search engine optimizers and content providers

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sebastian Schultheiß ◽  
Dirk Lewandowski
Keyword(s):  
Search Engine ◽  
Search Engines ◽  
Design Methodology ◽  
Web Search ◽  
Expert Interviews ◽  
Content Type ◽  
Search Engine Optimization ◽  
Stakeholder Groups ◽  
Web Search Engine ◽  
The Impact

PurposeIn commercial web search engine results rankings, four stakeholder groups are involved: search engine providers, users, content providers and search engine optimizers. Search engine optimization (SEO) is a multi-billion-dollar industry and responsible for making content visible through search engines. Despite this importance, little is known about its role in the interaction of the stakeholder groups.Design/methodology/approachWe conducted expert interviews with 15 German search engine optimizers and content providers, the latter represented by content managers and online journalists. The interviewees were asked about their perspectives on SEO and how they assess the views of users about SEO.FindingsSEO was considered necessary for content providers to ensure visibility, which is why dependencies between both stakeholder groups have evolved. Despite its importance, SEO was seen as largely unknown to users. Therefore, it is assumed that users cannot realistically assess the impact SEO has and that user opinions about SEO depend heavily on their knowledge of the topic.Originality/valueThis study investigated search engine optimization from the perspective of those involved in the optimization business: content providers, online journalists and search engine optimization professionals. The study therefore contributes to a more nuanced view on and a deeper understanding of the SEO domain.

Searching web documents using a summarization approach

2016 ◽  
Vol 12 (1) ◽  
pp. 83-101 ◽  
Author(s):  
Rani Qumsiyeh ◽  
Yiu-Kai Ng
Keyword(s):  
Search Engines ◽  
Web Search ◽  
Specific Information ◽  
Information Need ◽  
Search Query ◽  
Content Type ◽  
Additional Information ◽  
Search Results ◽  
User Query ◽  
Web Search Engines

Purpose The purpose of this paper is to introduce a summarization method to enhance the current web-search approaches by offering a summary of each clustered set of web-search results with contents addressing the same topic, which should allow the user to quickly identify the information covered in the clustered search results. Web search engines, such as Google, Bing and Yahoo!, rank the set of documents S retrieved in response to a user query and represent each document D in S using a title and a snippet, which serves as an abstract of D. Snippets, however, are not as useful as they are designed for, i.e. assisting its users to quickly identify results of interest. These snippets are inadequate in providing distinct information and capture the main contents of the corresponding documents. Moreover, when the intended information need specified in a search query is ambiguous, it is very difficult, if not impossible, for a search engine to identify precisely the set of documents that satisfy the user’s intended request without requiring additional information. Furthermore, a document title is not always a good indicator of the content of the corresponding document either. Design/methodology/approach The authors propose to develop a query-based summarizer, called QSum, in solving the existing problems of Web search engines which use titles and abstracts in capturing the contents of retrieved documents. QSum generates a concise/comprehensive summary for each cluster of documents retrieved in response to a user query, which saves the user’s time and effort in searching for specific information of interest by skipping the step to browse through the retrieved documents one by one. Findings Experimental results show that QSum is effective and efficient in creating a high-quality summary for each cluster to enhance Web search. Originality/value The proposed query-based summarizer, QSum, is unique based on its searching approach. QSum is also a significant contribution to the Web search community, as it handles the ambiguous problem of a search query by creating summaries in response to different interpretations of the search which offer a “road map” to assist users to quickly identify information of interest.

Children use second-and third-dimensional digital library interfaces

2016 ◽  
Vol 34 (1) ◽  
pp. 21-35 ◽  
Author(s):  
Kochiu Wu ◽  
Hung-Chun Chen
Keyword(s):  
User Interface ◽  
Digital Library ◽  
Digital Libraries ◽  
Cognitive Abilities ◽  
Information Seeking ◽  
Cognitive Skills ◽  
Ease Of Use ◽  
Search Performance ◽  
3D Navigation ◽  
Content Type

Purpose – The purpose of this paper is to explore children’s spatial cognitive abilities as they engaged in information-seeking behaviors on two-dimensional (2D) and three-dimensional (3D) digital interfaces. Design/methodology/approach – Children between the ages of seven and 11 were observed as they browsed either a 2D or 3D navigation interface for a children’s digital library. Data regarding their use of the overview function and depth cues were analyzed to reveal the relationships between search performance efficiency, precision, and effectiveness and the associative memory, visualization memory, and spatial visualization abilities of the user. Findings – Children spent less time using the 2D interface when compared to time spent using the 3D interface. Children exhibited better performance precision when using the 3D interface. Children applied exhaustive strategies and more varied cognitive skills across different tasks when using the 2D interface, and applied a more focussed approach when using the 3D interface. Originality/value – The cognitive abilities of children are not yet fully developed, so they require a unique user interface when browsing digital libraries. This study served the practical purpose of developing a game-like user interface for ease of use. Providing an effective overview function allows young users with less developed cognitive abilities to navigate informational cues. They can then build an effective mind map and implement efficient way-finding strategies.

Effectiveness of Google keyword suggestion on users’ relevance judgment

2016 ◽  
Vol 34 (2) ◽  
pp. 302-314 ◽  
Author(s):  
Rahmatollah Fattahi ◽  
Mehri Parirokh ◽  
Mohammd Hosien Dayyani ◽  
Abdolrasoul Khosravi ◽  
Mojgan Zareivenovel
Keyword(s):  
Search Engines ◽  
Query Expansion ◽  
Web Search ◽  
Information Need ◽  
Thinking Aloud ◽  
Content Type ◽  
Postgraduate Students ◽  
Relevance Judgment ◽  
Suggested Keywords ◽  
The Mean

Purpose – One of the most effective ways information retrieval (IR) systems including Web search engines can improve relevance performance is to provide their users with tools for facilitating query expansion. Search engines such as Google provide users with keyword suggest tools. This paper aims to investigate users’ criteria in relevance judgment regarding Google’s keywords suggest tool and to see how such keywords would lead to more relevant results from the viewpoint of users. Design/methodology/approach – Through a mixed method approach, quantitative and qualitative data were collected from 60 postgraduate students at Ferdowsi University of Mashhad, Iran, using four different instruments (questionnaire, thinking aloud technique, query logs and interviews). Findings – Among other criteria, the “relation between suggested keywords and the information need” (with the mean rate of 3.53 of four) was considered the most important by searchers in selecting suggested keywords for query expansion. Also, the “relation between suggested Keywords and the retrieved items” (with the mean rate of 3.62) was considered the second most important criterion in judging the relevance of the retrieved results. The participants agreed that the suggested keywords by Google improved the retrieval relevance. The content analysis of the participants’ aloud-thinking sessions and the interviews approved such findings. Originality/value – This research makes a contribution to the need of designers of IR systems regarding the use of add words for query expansion. It also helps librarians how to instruct searchers with expanding their queries to retrieve more relevant results. Another contribution of the study is the identification of a number of new relevance judgment criteria for Web-based environments.

Research and Improvement on Content-Based Web Search Engine

2012 ◽  
Vol 532-533 ◽  
pp. 1282-1286
Author(s):  
Zhi Chao Lin ◽  
Lei Sun ◽  
Xiao Liu
Keyword(s):  
Information Retrieval ◽  
Search Engine ◽  
Full Text ◽  
Search Engines ◽  
Query Expansion ◽  
Web Search ◽  
Text Search ◽  
Web Search Engine ◽  
Query Word ◽  
The Web

There is a lot of information contained in the World Wide Web. It has become a research focus to obtain the required related resources quickly and accurately from the web through the content-based search engines. Most current tools of full text web search engine, such as Lucene which is a widely used open source retrieval library in information retrieval field, are purely keyword based. This may not sufficient for users to retrieve in the web. In this paper, we employ a method to overcome the limitations of current full text search engines in represent of Lucene. We propose a Query Expansion and Information Retrieval approach which can help users to acquire more accurate contents from the web. The Query Expansion component finds expanded candidate words of the query word through WordNet which contains synonyms in several different senses; In the Information Retrieval component, the query word and its candidate words are used together as the input of the search module to get the result items. Furthermore, we can put the result items into different classes based on the expansion. Some experiments and the results are described in the late part of this paper.

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