scholarly journals Design of Efficient Web Search System Based on Reliable Online Community

2012 ◽  
Vol 37 (1B) ◽  
pp. 67-74 ◽  
Author(s):  
Young-An Kim ◽  
Sang-Kwan Park ◽  
Sang-Hoon Lee
Keyword(s):  
Online Community ◽  
Web Search ◽  
Search System

scholarly journals Identification of Trending Topics Using Periodically Collected Twitter Data

2018 ◽  
Vol 7 (3.12) ◽  
pp. 205
Author(s):  
Ranjini V ◽  
Soundarya R ◽  
S Karthika ◽  
S Mohanavalli ◽  
Srividhya .
Keyword(s):  
Online Community ◽  
Web Search ◽  
Pattern Mining ◽  
Warning System ◽  
Frequent Pattern Mining ◽  
Frequent Pattern ◽  
Trend Prediction ◽  
Search System ◽  
Twitter Data ◽  
Trending Topics

Social media is an interactive personal tool to articulate an individual's cognizance. This project involves one such micro blogging platform, Twitter. Trends can simply be defined as the frequently mentioned topics throughout the stream of user activities. Mining twitter data for identifying trending topics provides an overview of the topics and issues that are currently popular within the online community. Therefore, the most effective and suitable methodology should be implemented to identify the short term high intensity discussion topic. The trigrams or higher order n-grams are used to determine the trending topic. Twitter Streaming API is used to collect data from the Twitter accounts using API keys and the formatted tweets are stored in a non SQL database. Subsequent steps include data cleansing followed by stemming. The processed data is subjected to trend prediction algorithms like DB Scan, Frequent Pattern Mining, Trees(fuzzy/inductive/decision), Soft frequent pattern mining and empirical statistics such as Frequency metric, TF-IDF, Normalized term frequency and Entropy based on the key parameters to identify the most trending event within a period of time. Thus, the trending topics can be detected with a reasonably close approximation to the expected outcome.  This can be used in detecting and predicting events for an early warning system (or) prediction tools and also artificially intelligent services like web search system or recognition systems.  

Based on DNS of a Layered Web Search Engine Study

2014 ◽  
Vol 971-973 ◽  
pp. 1870-1873
Author(s):  
Xiao Gang Dong
Keyword(s):  
Search Engine ◽  
Web Search ◽  
Web Pages ◽  
Distributed Architecture ◽  
Search System ◽  
Web Search Engine ◽  
Original Idea ◽  
Commercial Search Engine ◽  
New System ◽  
The Web

Web search engine based on DNS, the standard proposed solution of IETF for public web search system, is introduced in this paper. Now no web search engine can cover more than 60 percent of all the pages on Internet. The update interval of most pages database is almost one month. This condition hasn't changed for many years. Converge and recency problems have become the bottleneck problem of current web search engine. To solve these problems, a new system, search engine based on DNS is proposed in this paper. This system adopts the hierarchical distributed architecture like DNS, which is different from any current commercial search engine. In theory, this system can cover all the web pages on Internet. Its update interval could even be one day. The original idea, detailed content and implementation of this system all are introduced in this paper.

Collaborative search using an implicitly formed academic network

2014 ◽  
Vol 66 (5) ◽  
pp. 537-552 ◽  
Author(s):  
Somu Renugadevi ◽  
T.V. Geetha ◽  
R.L. Gayathiri ◽  
S. Prathyusha ◽  
T. Kaviya
Keyword(s):  
Design Methodology ◽  
Web Search ◽  
Community Formation ◽  
Search System ◽  
Search Behaviour ◽  
Content Type ◽  
Collaborative Search ◽  
Research Findings ◽  
Academic Network ◽  
Dynamic Updating

Purpose – The purpose of this paper is to propose the Collaborative Search System that attempts to achieve collaboration by implicitly identifying and reflecting search behaviour of collaborators in an academic network that is automatically and dynamically formed. By using the constructed Collaborative Hit Matrix (CHM), results are obtained that are based on the search behaviour and earned preferences of specialist communities of researchers, which are relevant to the user's need and reduce the time spent on bad links. Design/methodology/approach – By using the Digital Bibliography Library Project (DBLP), the research communities are formed implicitly and dynamically based on the users’ research presence in the search environment and in the publication scenario, which is also used to assign users’ roles and establish links between the users. The CHM, to store the hit count and hit list of page results for queries, is also constructed and updated after every search session to enhance the collaborative search among the researchers. Findings – The implicit researchers community formation, the assignment and dynamic updating of roles of the researchers based on research, search presence and search behaviour on the web as well as the usage of these roles during Collaborative Web Search have highly improved the relevancy of results. The CHM that holds the collaborative responses provided by the researchers on the search query results to support searching distinguishes this system from others. Thus the proposed system considerably improves the relevancy and reduces the time spent on bad links, thus improving recall and precision. Originality/value – The research findings illustrate the better performance of the system, by connecting researchers working in the same field and allowing them to help each other in a web search environment.

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