scholarly journals Concept extraction and clustering for search result organization and virtual community construction

2012 ◽  
Vol 9 (1) ◽  
pp. 323-355 ◽  
Author(s):  
Shihn-Yuarn Chen ◽  
Chia-Ning Chang ◽  
Yi-Hsiang Nien ◽  
Hao-Ren Ke
Keyword(s):  
Virtual Community ◽  
Value Added ◽  
Visual Presentation ◽  
Previous Approach ◽  
Concept Extraction ◽  
Semantic Correlation ◽  
Search Results ◽  
Search Result ◽  
Community Construction ◽  
Log Likelihood

This study proposes a concept extraction and clustering method, which improves Topic Keyword Clustering by using Log Likelihood Ratio for semantic correlation and Bisection K-Means for document clustering. Two value-added services are proposed to show how this approach can benefit information retrieval (IR) systems. The first service focuses on the organization and visual presentation of search results by clustering and bibliographic coupling. The second one aims at constructing virtual research communities and recommending significant papers to researchers. In addition to the two services, this study conducts quantitative and qualitative evaluations to show the feasibility of the proposed method; moreover, comparison with the previous approach is also performed. The experimental results show that the accuracy of the proposed method for search result organization reaches 80%, outperforming Topic Keyword Clustering. Both the precision and recall of virtual community construction are higher than 70%, and the accuracy of paper recommendation is almost 90%.

The enigmatic journal index: when a negative search result is positive

2021 ◽  
Vol 39 (3) ◽  
pp. 293-295
Author(s):  
Max McMaster
Keyword(s):  
Positive Outcome ◽  
Search Results ◽  
Journal Editors ◽  
Search Result

Journal editors’ use of cumulative journal indexes is quite different to that of the traditional readership. Journal editors use such indexes as either a source of inspiration or a tool for verifying if and when a topic has (or has not) been covered in their journal. In many cases, finding few or no search results is a positive outcome, as this provides editors with the scope and impetus to commission articles on topics that have either not been covered in their journal for several years or not covered at all. Three examples are provided.

scholarly journals IMPLEMENTASI ALGORITMA GOOGLE LATENT SEMANTIC DISTANCE UNTUK EKSTRAKSI RANGKAIAN KATA KUNCI ARTIKEL JURNAL ILMIAH

2018 ◽  
Vol 2 (2) ◽  
pp. 186
Author(s):  
Novario Jaya Perdana
Keyword(s):  
Search Engine ◽  
Search Engines ◽  
Semantic Distance ◽  
Relevant Information ◽  
High Accuracy ◽  
Hard Work ◽  
The Internet ◽  
Search Results ◽  
Search Result

The accuracy of search result using search engine depends on the keywords that are used. Lack of the information provided on the keywords can lead to reduced accuracy of the search result. This means searching information on the internet is a hard work. In this research, a software has been built to create document keywords sequences. The software uses Google Latent Semantic Distance which can extract relevant information from the document. The information is expressed in the form of specific words sequences which could be used as keyword recommendations in search engines. The result shows that the implementation of the method for creating document keyword recommendation achieved high accuracy and could finds the most relevant information in the top search results.

Spatio-Temporal Based Personalization for Mobile Search

2012 ◽  
pp. 386-409 ◽  
Author(s):  
Ourdia Bouidghaghen ◽  
Lynda Tamine
Keyword(s):  
Information Retrieval ◽  
Contextual Information ◽  
The Internet ◽  
Search Results ◽  
Search Result ◽  
Retrieval Systems ◽  
Information Retrieval Systems ◽  
Spatio Temporal ◽  
Mobile Context

The explosion of the information available on the Internet has made traditional information retrieval systems, characterized by one size fits all approaches, less effective. Indeed, users are overwhelmed by the information delivered by such systems in response to their queries, particularly when the latter are ambiguous. In order to tackle this problem, the state-of-the-art reveals that there is a growing interest towards contextual information retrieval (CIR) which relies on various sources of evidence issued from the user’s search background and environment, in order to improve the retrieval accuracy. This chapter focuses on mobile context, highlights challenges they present for IR, and gives an overview of CIR approaches applied in this environment. Then, the authors present an approach to personalize search results for mobile users by exploiting both cognitive and spatio-temporal contexts. The experimental evaluation undertaken in front of Yahoo search shows that the approach improves the quality of top search result lists and enhances search result precision.

Inside the Project Management Institute

2016 ◽  
pp. 1136-1141
Author(s):  
Deborah Walker ◽  
Dave Garrett
Keyword(s):  
Social Media ◽  
Portfolio Management ◽  
Change Agents ◽  
Virtual Community ◽  
Value Added ◽  
For Profit ◽  
Not For Profit ◽  
Project Management Institute ◽  
Social Media Platforms ◽  
Membership Association

PMI is the world's leading not-for-profit professional membership association for the project, program, and portfolio management profession. Now in its 46th year, the association provides global advocacy, collaboration, education, and research to more than 2.9 million professionals working in nearly every country in the world. To better support project practitioners in their role as “change agents,” PMI utilizes popular social media platforms, as well as a robust virtual community. Through social media, PMI creates an environment in which project practitioners create, curate, and share strong value-added content, take part in well-informed discussions, and collaborate to seek effective solutions.

scholarly journals Data Presentation Structures in Specialised Dictionaries: Law Dictionaries with Communicative Functions / Datenpräsentationsstrukturen in Fachwörterbüchern: Rechtswörterbücher mit einer kommunikativen Funktion / La structure de la présentation des données dans les dictionnaires spécialisés

2015 ◽  
Vol 31 (1) ◽  
pp. 200-216
Author(s):  
Sandro Nielsen
Keyword(s):  
Functional Data ◽  
Data Types ◽  
Data Presentation ◽  
Search Results ◽  
Search Result ◽  
Visual Hierarchy ◽  
Communicative Functions

Abstract Theoretical lexicographers have developed a range of elaborate structures to describe the arrangement of data inside dictionaries, in particular in dictionary articles. However, most of these structures have been developed on the basis of detailed analyses of print dictionaries and relatively little has been said about the arrangement of data in e-dictionaries. The relevant data types are lexicographical data providing help concerning the function(s) and use of dictionaries on search results pages. In order to create a visual hierarchy on screen that makes the most important search result data stand out, lexicographers should prioritize functional data that are directly related to and support the function(s) of dictionaries on a need-to-have/niceto- have basis, because data presentation structures with functional focus may better help users achieve their intended goals, i.e. finding answers to problems in communicative situations. One result is that lexicographers can analyse and describe the visual hierarchy in terms of data presentation fields and search zones, even though some search results may be described as non-articles.

Website Quality Evaluation Based on Search Engine Queries using Web Rank Position Algorithm (WRPA)

2016 ◽  
Vol 4 (1) ◽  
pp. 224
Author(s):  
Chandran M ◽  
Ramani A. V
Keyword(s):  
Search Engine ◽  
Search Engines ◽  
Quality Evaluation ◽  
Research Work ◽  
Search Query ◽  
Website Quality ◽  
Search Results ◽  
Search Result ◽  
Different Types

<p>The research work is about to test the quality of the website and to improve the quality by analyzing the hit counts, impressions, clicks, count through rates and average positions. This is accomplished using WRPA and SEO technique. The quality of the website mainly lies on the keywords which are present in it. The keywords can be of a search query which is typed by the users in the search engines and based on these keywords, the websites are displayed in the search results. This research work concentrates on bringing the particular websites to the first of the search result in the search engine. The website chosen for research is SRKV. The research work is carried out by creating an index array of Meta tags. This array will hold all the Meta tags. All the search keywords for the website from the users are stored in another array. The index array is matched and compared with the search keywords array. From this, hit to count is calculated for the analysis. Now the calculated hit count and the searched keywords will be analyzed to improve the performance of the website. The matched special keywords from the above comparison are included in the Meta tag to improve the performance of the website. Again all the Meta tags and newly specified keywords in the index array are matched with the SEO keywords. If this matches, then the matched keyword will be stored for improving the quality of the website. Metrics such as impressions, clicks, CTR, average positions are also measured along with the hit counts. The research is carried out under different types of browsers and different types of platforms. Queries about the website from different countries are also measured. In conclusion, if the number of the clicks for the website is more than the average number of clicks, then the quality of the website is good. This research helps in improvising the keywords using WRPA and SEO and thereby improves the quality of the website easily.</p>

Augmenting the visual presentation of Web search results

2010 ◽  
Author(s):  
Anwar Alhenshiri ◽  
Stephen Brooks ◽  
Carolyn Watters ◽  
Michael Shepherd
Keyword(s):  
Web Search ◽  
Visual Presentation ◽  
Search Results

scholarly journals Instagram Image Filtration with Computer Vision

2021 ◽  
Author(s):  
Tanjimul Ahad Asif ◽  
Baidya Nath Saha
Keyword(s):  
Image Processing ◽  
Human Face ◽  
Image Processing Techniques ◽  
Search Results ◽  
Search Result ◽  
Face Images ◽  
Image Filtration ◽  
The Face ◽  
Processing Techniques ◽  
Human Faces

Instagram is one of the famous and fast-growing media sharing platforms. Instagram allows users to share photos and videos with followers. There are plenty of ways to search for images on Instagram, but one of the most familiar ways is ’hashtag.’ Hashtag search enables the users to find the precise search result on Instagram. However, there are no rules for using the hashtag; that is why it often does not match the uploaded image, and for this reason, Users are unable to find the relevant search results. This research aims to filter any human face images on search results based on hashtags on Instagram. Our study extends the author’s [2] work by implementing image processing techniques that detect human faces and separate the identified images on search results based on hashtags using the face detection technique.

scholarly journals Improving Search Engine Efficiency through Contextual Factor Selection

AI Magazine ◽  
2021 ◽  
Vol 42 (2) ◽  
pp. 50-58
Author(s):  
Anxiang Zeng ◽  
Han Yu ◽  
Qing Da ◽  
Yusen Zhan ◽  
Yang Yu ◽  
...  
Keyword(s):  
Search Engine ◽  
Large Scale ◽  
Learning To Rank ◽  
Contextual Factor ◽  
System Response ◽  
Search Query ◽  
Previous Approach ◽  
Engine Efficiency ◽  
Search Result ◽  
Selection Of

Learning to rank (LTR) is an important artificial intelligence (AI) approach supporting the operation of many search engines. In large-scale search systems, the ranking results are continually improved with the introduction of more factors to be considered by LTR. However, the more factors being considered, the more computation resources required, which in turn, results in increased system response latency. Therefore, removing redundant factors can significantly improve search engine efficiency. In this paper, we report on our experience incorporating our Contextual Factor Selection (CFS) deep reinforcement learning approach into the Taobao e-commerce platform to optimize the selection of factors based on the context of each search query to simultaneously maintaining search result quality while significantly reducing latency. Online deployment on Taobao.com demonstrated that CFS is able to reduce average search latency under everyday use scenarios by more than 40% compared to the previous approach with comparable search result quality. Under peak usage during the Single’s Day Shopping Festival (November 11th) in 2017, CFS reduced the average search latency by 20% compared to the previous approach.

scholarly journals "DNS SEHAT" Implementation on Automatic Replicated Recursive Domain Name System on PT. X

2019 ◽  
Author(s):  
Muhammad Ilham Verardi Pradana
Keyword(s):  
Search Engine ◽  
Search Engines ◽  
The Other ◽  
The Internet ◽  
Domain Name System ◽  
Domain Name ◽  
Search Results ◽  
Search Result ◽  
Google Search

Thanks to the existence of Search engines, all of informations and datas could be easily found in the internet, one of the search engine that users use the most is Google. Google still be the most popular search engine to provide any informations available on the internet. The search result that Google provide, doesn't always give the result we wanted. Google just displayed the results based on the keyword we type. So sometimes, they show us the negative contents on the internet, such as pornography, pornsites, and many more that seems to be related to the keyword, whether the title or the other that makes the result going that way. In this paper, we will implement the "DNS SEHAT" to pass along client's request queries so the Google search engine on the client's side will provide more relevant search results without any negative contents.

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