ESAP: A Novel Approach for Cross-Platform Event Dissemination Trend Analysis Between Social Network and Search Engine

2016 ◽  
pp. 489-504 ◽  
Author(s):  
Yan Tang ◽  
Pengju Ma ◽  
Boyuan Kong ◽  
Wenqian Ji ◽  
Xiaofeng Gao ◽  
...  
Keyword(s):  
Social Network ◽  
Trend Analysis ◽  
Search Engine ◽  
Novel Approach ◽  
Cross Platform

Structural change in search engine news service: a social network perspective

2012 ◽  
Vol 22 (2) ◽  
pp. 160-178 ◽  
Author(s):  
Yong-Seok Hwang ◽  
Dong-Hee Shin ◽  
Yeolib Kim
Keyword(s):  
Social Network ◽  
Structural Change ◽  
Search Engine ◽  
News Service

Aspects of Various Community Detection Algorithms in Social Network Analysis

2019 ◽  
pp. 327-341
Author(s):  
Nicole Belinda Dillen ◽  
Aruna Chakraborty
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Community Detection ◽  
Overlapping Community Detection ◽  
Detection Algorithms ◽  
Novel Approach ◽  
Recent Developments ◽  
Overlapping Community ◽  
Related Individuals

One of the most important aspects of social network analysis is community detection, which is used to categorize related individuals in a social network into groups or communities. The approach is quite similar to graph partitioning, and in fact, most detection algorithms rely on concepts from graph theory and sociology. The aim of this chapter is to aid a novice in the field of community detection by providing a wider perspective on some of the different detection algorithms available, including the more recent developments in this field. Five popular algorithms have been studied and explained, and a recent novel approach that was proposed by the authors has also been included. The chapter concludes by highlighting areas suitable for further research, specifically targeting overlapping community detection algorithms.

A Novel Approach to End-to-End Facial Recognition Framework with Virtual Search Engine ElasticSearch

2021 ◽  
pp. 454-470
Author(s):  
Dat Nguyen Van ◽  
Son Nguyen Trung ◽  
Anh Pham Thi Hong ◽  
Thao Thu Hoang ◽  
Ta Minh Thanh
Keyword(s):  
Search Engine ◽  
Facial Recognition ◽  
Novel Approach ◽  
End To End

Implementing Background Net with Knowware System for Personalized Keyword Support

2011 ◽  
Vol 2 (1) ◽  
pp. 77-90
Author(s):  
Yuan Chen ◽  
Liya Ding ◽  
Sio-Long Lo ◽  
Dickson K.W. Chiu
Keyword(s):  
Search Engine ◽  
Undirected Graph ◽  
Target System ◽  
Component Reuse ◽  
Personal Preference ◽  
Development Tool ◽  
Novel Approach ◽  
The Given ◽  
Contextual Association

This article proposes a novel approach that combines user’s instant requirement described in keywords with her or his long-term knowledge background to better serve article selection based on personal preference. The knowledge background is represented as a weighted undirected graph called background net that captures the contextual association of words that appear in the articles recommended by the user through incremental learning. With a background net of user constructed, a keyword from the user is personalized to a fuzzy set that represents contextual association of the given keyword to other words involved in the user’s background net. An article evaluation with personal preference can be achieved by evaluating similarity between personalized keyword set based on user’s background net and a candidate article. The proposed approach makes it possible to construct a search engine optimizer running on the top of search engines to adjust search results, and offer the potential to be integrated with existing search engine techniques to achieve better performance. The target system of personalized article selection can be automatically constructed using Knowware System which is a development tool of KBS for convenient modeling and component reuse.

Social Network Mining from the Web

2011 ◽  
pp. 149-175 ◽  
Author(s):  
Yutaka Matsuo ◽  
Junichiro Mori ◽  
Mitsuru Ishizuka
Keyword(s):  
Social Network ◽  
Search Engine ◽  
Relevant Information ◽  
Web Content ◽  
Message Boards ◽  
Network Information ◽  
Network Mining ◽  
Social Network Mining ◽  
The Social ◽  
The Web

This chapter describes social network mining from the Web. Since the end of the 1990s, several attempts have been made to mine social network information from e-mail messages, message boards, Web linkage structure, and Web content. In this chapter, we specifically examine the social network extraction from the Web using a search engine. The Web is a huge source of information about relations among persons. Therefore, we can build a social network by merging the information distributed on the Web. The growth of information on the Web, in addition to the development of a search engine, opens new possibilities to process the vast amounts of relevant information and mine important structures and knowledge.

A Festival-Wide Social Network Using 2D Barcodes, Mobile Phones and Situated Displays

2011 ◽  
Vol 3 (3) ◽  
pp. 14-30 ◽  
Author(s):  
Jakob Eg Larsen ◽  
Arkadiusz Stopczynski
Keyword(s):  
Social Network ◽  
Mobile Phones ◽  
Low Cost ◽  
The Novel ◽  
Client Application ◽  
Mobile Client ◽  
Music Festival ◽  
Network Applications ◽  
Network Interaction ◽  
Novel Approach

This paper reports on the authors’ experiences with an exploratory prototype festival-wide social network. Unique 2D barcodes were applied to wristbands and mobile phones to uniquely identify the festival participants at the CO2PENHAGEN music festival in Denmark. The authors describe experiences from initial use of a set of social network applications involving participant profiles, a microblog and images shared on situated displays, and competitions created for the festival. The pilot study included 73 participants, each creating a unique profile. The novel approach had potential to enable anyone at the festival to participate in the festival-wide social network, as participants did not need any special hardware or mobile client application to be involved. The 2D barcodes was found to be a feasible low-cost approach for unique participant identification and social network interaction. Implications for the design of future systems of this nature are discussed.

Novel approach for search engine

2016 ◽  
Author(s):  
Yoichi Sato ◽  
Kanji Otsuka ◽  
Kaoru Kobayashi ◽  
Toshiyuki Kouchi ◽  
Minoru Uwai ◽  
...  
Keyword(s):  
Search Engine ◽  
Novel Approach

scholarly journals A Cross layer QoS Framework for Heterogeneous IoT Environment

2019 ◽  
Vol 9 (2) ◽  
pp. 1972-1979
Keyword(s):  
Service Level ◽  
Cross Layer ◽  
Service Provisioning ◽  
Critical Research ◽  
Distributed Decision Making ◽  
Cross Domain ◽  
Novel Approach ◽  
Cross Platform ◽  
And Storage

Internet of Things (IoT) is one of the fast growing technological paradigm in terms of architecture, standards, protocols, infrastructure deployment, Quality of Service (QoS), Service Level Agreements (SLAs), service provisioning, cross domain and cross platform implementations. IoT involves the techniques and technologies for sensing, actuation, communication, computation, networking and storage. In such a demanding environment the need for cross layer QoS functionalities are essential to address the issues like resources, mobility, security and energy management. The detailed review of literatures on IoT architectures and QoS implementations is made and it is observed that there is a need for cross layer QoS model in IoT environments and is one of the critical research challenges. A novel approach to address the above challenge(s) in an IoT environment requires an appropriate lathering of functional modules to different layers to meet different QoS requirements. Hence we propose a novel cross layer QoS framework supporting adaptable and distributed decision making in the IoT environment as a cross layer implementation addressing energy optimization and bandwidth efficiency. The results are verified by implementing the proposed framework in realistic IoT systems for verifying QoS parameters like delay, energy and bandwidth.

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