Exploring Semantic Characteristics of Socially Constructed Knowledge Repository to Optimize Web Search

2013 ◽  
pp. 250-271
Author(s):  
Dengya Zhu ◽  
Heinz Dreher
Keyword(s):  
Web Search ◽  
Experimental Results ◽  
Training Data ◽  
Search Term ◽  
Short Term ◽  
User Perspective ◽  
Knowledge Repository ◽  
Search Results ◽  
Socially Constructed ◽  
Search Terms

Short-term queries preferred by most users often result in a list of Web search results with low precision from a user perspective. The purpose of this research is to improve the relevance of Web search results via search-term disambiguation and ontological filtering of search results based on socially constructed search concepts. A Special Search Browser (SSB) is developed where semantic characteristics of the socially constructed knowledge repository are extracted to form a category-document set. kNN is employed with the extracted category-documents as training data to classify Web results. Users’ selected categories are employed to present the search results. Experimental results based on five experts’ judgments over 250 hits from Yahoo! API demonstrate that utilizing the socially constructed search concepts to categorize and filter search results can improve precision by 23.5%, from Yahoo’s 41.7% to 65.2% of SSB based on the results of five selected ambiguous search-terms.

Bibliometric Analysis of Lean, Agile, and Leagile Supply Chains in Automobile Industry (1990 - 2017)

2020 ◽  
pp. 1746-1770
Author(s):  
Venkatesh Iyengar ◽  
S. Vijayakumar Bharathi
Keyword(s):  
Supply Chains ◽  
Bibliometric Analysis ◽  
Automobile Industry ◽  
Search Term ◽  
Search Results ◽  
Search Terms ◽  
Efficient Performance ◽  
Academic Publications ◽  
Data Statistics ◽  
Legal Strategies

This article describes how organizations embrace various supply chain strategies aiming at effective and efficient performance outcomes for gaining competitive advantage. The authors conducted an extensive search for academic publications on lean, agile, and leagile (hybrid) supply chains in context with automobile industries, published since year 1990 in reliable repositories such as Google Scholar, Scopus and ResearchGate. None of these papers used bibliometric analysis on the topic. This paper systematically maps, publications on lean, agile, and legal strategies in automobile industry published during 1990–2017. A five-step process is followed, namely (i) defining appropriate search terms, (ii) initial search results, (iii) refinement of search results, (iv) initial data, statistics, and (v) data analysis; adopted for inclusion of relevant documents for publication and citation analysis. Selected documents include primary search term ‘automobile' along with associated secondary terms such as ‘lean', ‘agile', ‘lean and agile', and ‘leagile' as part of the title, abstract, or keywords. The analysis finds several documents on lean or agile strategies, but only one document exists on ‘leagile' paradigm. Maximum articles are contributed on engineering subjects followed by business, management and accounting and computer sciences. Large publication and high citation counts were observed for lean from United States and Chinese authors, whereas Indian authors contributed in agile studies. This article identifies areas of current research interests discussing crucial contributions by several authors' and provides potential directions for further research investigations in the field.

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.

Bibliometric Analysis of Lean, Agile, and Leagile Supply Chains in Automobile Industry (1990 - 2017)

2018 ◽  
Vol 11 (3) ◽  
pp. 22-45 ◽  
Author(s):  
Venkatesh Iyengar ◽  
S. Vijayakumar Bharathi
Keyword(s):  
Supply Chains ◽  
Bibliometric Analysis ◽  
Automobile Industry ◽  
Performance Outcomes ◽  
Search Term ◽  
Search Results ◽  
Search Terms ◽  
Efficient Performance ◽  
Academic Publications ◽  
Legal Strategies

This article describes how organizations embrace various supply chain strategies aiming at effective and efficient performance outcomes for gaining competitive advantage. The authors conducted an extensive search for academic publications on lean, agile, and leagile (hybrid) supply chains in context with automobile industries, published since year 1990 in reliable repositories such as Google Scholar, Scopus and ResearchGate. None of these papers used bibliometric analysis on the topic. This paper systematically maps, publications on lean, agile, and legal strategies in automobile industry published during 1990–2017. A five-step process is followed, namely (i) defining appropriate search terms, (ii) initial search results, (iii) refinement of search results, (iv) initial data, statistics, and (v) data analysis; adopted for inclusion of relevant documents for publication and citation analysis. Selected documents include primary search term ‘automobile' along with associated secondary terms such as ‘lean', ‘agile', ‘lean and agile', and ‘leagile' as part of the title, abstract, or keywords. The analysis finds several documents on lean or agile strategies, but only one document exists on ‘leagile' paradigm. Maximum articles are contributed on engineering subjects followed by business, management and accounting and computer sciences. Large publication and high citation counts were observed for lean from United States and Chinese authors, whereas Indian authors contributed in agile studies. This article identifies areas of current research interests discussing crucial contributions by several authors' and provides potential directions for further research investigations in the field.

scholarly journals خرائط الكلمات المفتاحية في بيئة الإنترنت لأسئلة البحث الأكثر شيوعاً حول " فيروس كورونا"

2020 ◽  
pp. 70-92
Author(s):  
طلال ناظم الزهيري
Keyword(s):  
Google Trends ◽  
Search Term ◽  
Global Level ◽  
Search Results ◽  
Search Terms ◽  
Internet Users ◽  
Search For Information ◽  
Health Situation ◽  
Number Of Iterations ◽  
Analyze Data

Keywords maps are common search phrases, and one of the most important indicators of the importance of topics and the level of attracting them to the interests of users at the global level. Today, after the outbreak of Coronavirus, it was necessary to know the global interest in this virus, and what are the phrases and keyword maps used by the Arab users in the search engines in the stage of collecting information about this disease, so, this study aims to identify the nature of inquiries about the virus used by internet users and classify them according to the considerations of number of iterations, as well as mapping the keywords for common search terms about Coronavirus in Arabic and trying to use them in improving access to appropriate information. The study uses [Google Trends] to analyze data and access search results for the selected search term. The study reached a set of conclusions, the most important of which was: The search term (Coronavirus) is the most preferred search term in the search for information about this disease for the Arab users. In addition, the study recommends that the websites that interested in the health situation should take the advantages of the keywords maps that the study reached to include them as descriptions of awareness topics and news about the virus to ensure the highest views.

scholarly journals Semantics Discovery via Human Computation Games

Semantic Web ◽  
2013 ◽  
pp. 286-308 ◽  
Author(s):  
Jakub Šimko ◽  
Michal Tvarožek ◽  
Mária Bieliková
Keyword(s):  
Computer Games ◽  
Web Search ◽  
Human Computation ◽  
Search Term ◽  
Search Game ◽  
Search Terms ◽  
Qualitative Feedback ◽  
Novel Approach ◽  
Series Of Experiments ◽  
Relationship Network

The effective acquisition of (semantic) metadata is crucial for many present day applications. Games with a purpose address this issue by transforming computational problems into computer games. The authors present a novel approach to metadata acquisition via Little Search Game (LSG) – a competitive web search game, whose purpose is the creation of a term relationship network. From a player perspective, the goal is to reduce the number of search results returned for a given search term by adding negative search terms to a query. The authors describe specific aspects of the game’s design, including player motivation and anti-cheating issues. The authors have performed a series of experiments with Little Search Game, acquired real-world player input, gathered qualitative feedback from the players, constructed and evaluated term relationship network from the game logs and examined the types of created relationships.

scholarly journals Short‐term railway passenger demand forecast using improved Wasserstein generative adversarial nets and web search terms

2021 ◽  
Vol 15 (3) ◽  
pp. 432-445
Author(s):  
Fenling Feng ◽  
Jiaqi Zhang ◽  
Chengguang Liu ◽  
Wan Li ◽  
Qiwei Jiang
Keyword(s):  
Web Search ◽  
Demand Forecast ◽  
Short Term ◽  
Passenger Demand ◽  
Search Terms ◽  
Railway Passenger

Senses of “Selfie” Around the World From Web Search Patterns Over Extended Time

2018 ◽  
pp. 249-295
Author(s):  
Shalin Hai-Jew
Keyword(s):  
Web Search ◽  
Search Term ◽  
Extended Time ◽  
Social Phenomena ◽  
Search Terms ◽  
Time Patterns ◽  
Search Patterns ◽  
The World ◽  
Technological Affordances ◽  
Google Search

When social phenomena and practices go viral, like “selfies,” they instantiate in different locations around the world in different ways based on cultural differences, technological affordances, and other factors. When people go to search for “selfie” on Google Search, they are thinking different things as well. On Google Correlate, it is possible to identify the top correlating search terms that pattern-match the time patterns for the seeding search term. Based in this big data, these search term correlates (associated over extended time) provide a sense of the “group mind” around a particular topic.

scholarly journals Semantics Discovery via Human Computation Games

2011 ◽  
Vol 7 (3) ◽  
pp. 23-45 ◽  
Author(s):  
Jakub Šimko ◽  
Michal Tvarožek ◽  
Mária Bieliková
Keyword(s):  
Computer Games ◽  
Web Search ◽  
Human Computation ◽  
Search Term ◽  
Search Game ◽  
Search Terms ◽  
Qualitative Feedback ◽  
Novel Approach ◽  
Series Of Experiments ◽  
Relationship Network

The effective acquisition of (semantic) metadata is crucial for many present day applications. Games with a purpose address this issue by transforming computational problems into computer games. The authors present a novel approach to metadata acquisition via Little Search Game (LSG) – a competitive web search game, whose purpose is the creation of a term relationship network. From a player perspective, the goal is to reduce the number of search results returned for a given search term by adding negative search terms to a query. The authors describe specific aspects of the game’s design, including player motivation and anti-cheating issues. The authors have performed a series of experiments with Little Search Game, acquired real-world player input, gathered qualitative feedback from the players, constructed and evaluated term relationship network from the game logs and examined the types of created relationships.

A Study on Web Searching

2008 ◽  
pp. 1926-1937
Author(s):  
Shanfeng Chu ◽  
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.

scholarly journals An Integrated Search Framework for Leveraging the Knowledge-Based Web Ecosystem

2020 ◽  
Vol 24 ◽  
Author(s):  
Dengya Zhu ◽  
Shastri Lakshman Nimmagadda ◽  
Torsten Reiners ◽  
Amit Rudra
Keyword(s):  
Information Retrieval ◽  
Web Search ◽  
Relevant Information ◽  
Database Search ◽  
The Internet ◽  
Search Process ◽  
Search Results ◽  
Knowledge Based ◽  
Search Terms ◽  
Effective Use

The explosion of information constrains the judgement of search terms associated with Knowledge-Based Web Ecosystem (KBWE), making the retrieval of relevant information and its knowledge management challenging. The existing information retrieval (IR) tools and their fusion in a framework need attention, in which search results can effectively be managed. In this article, we demonstrate the effective use of information retrieval services by a variety of users and agents in various KBWE scenarios. An innovative Integrated Search Framework (ISF) is proposed, which utilises crawling strategies, web search technologies and traditional database search methods. Besides, ISF offers comprehensive, dynamic, personalized, and organization-oriented information retrieval services, ranging from the Internet, extranet, intranet, to personal desktop. In this empirical research, experiments are carried out demonstrating the improvements in the search process, as discerned in the conceptual ISF. The experimental results show improved precision compared with other popular search engines.

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