research-article

Generating associative ripples of relevant information from a variety of data streams by throwing a heuristic stone

Authors:

Jianming YongAuthors Info & Claims

ICUIMC '11: Proceedings of the 5th International Conference on Ubiquitous Information Management and Communication

Article No.: 59, Pages 1 - 7

https://doi.org/10.1145/1968613.1968685

Published: 21 February 2011 Publication History

Abstract

Recently, the vast dialog in the microblog, such as twitter, Facebook has become increasingly popular. As we post more messages in microblogs, information is spreading more quickly and widely. These widely spread and diversified contents could be viewed as data streams, which have become an important part of the Internet resources. However, these separated data streams are littery and meaningless, so we need to collect and organize them together to provide us with meaningful information. It is hard to imagine that we could find useful information by simply inputting a few keywords into a search engine in such a stream environment. In this study, we try to find a way to seek the information related to users' personal and current interests and needs among these data streams and provide users with other more relevant information. We introduce a set of metaphors to represent a variety of data streams in different levels, and define two new metaphors: heuristic stone and associative ripple to assist the seeking process and describe the results. Based on these, we further propose two algorithms for the information seeking and processing, and discuss a scenario of the information seeking process that utilizes the proposed metaphors and algorithms.

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Cited By

Sun XYan KZhou X(2020)Fault Detection and Diagnosis of Chillers with S&D Convolutional Neural Network2020 International Conferences on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData) and IEEE Congress on Cybermatics (Cybermatics)10.1109/iThings-GreenCom-CPSCom-SmartData-Cybermatics50389.2020.00141(829-836)Online publication date: Nov-2020
https://doi.org/10.1109/iThings-GreenCom-CPSCom-SmartData-Cybermatics50389.2020.00141
Yuan YHuang JMa XYan K(2020)Children's Drawing Psychological Analysis using Shallow Convolutional Neural Network2020 International Conferences on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData) and IEEE Congress on Cybermatics (Cybermatics)10.1109/iThings-GreenCom-CPSCom-SmartData-Cybermatics50389.2020.00120(692-698)Online publication date: Nov-2020
https://doi.org/10.1109/iThings-GreenCom-CPSCom-SmartData-Cybermatics50389.2020.00120
Zhou XJin Q(2017)A heuristic approach to discovering user correlations from organized social stream dataMultimedia Tools and Applications10.1007/s11042-014-2153-576:9(11487-11507)Online publication date: 1-May-2017
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Index Terms

Generating associative ripples of relevant information from a variety of data streams by throwing a heuristic stone
1. Information systems
  1. Information retrieval
  2. Information systems applications
    1. Data mining
      1. Clustering

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Published In

cover image ACM Conferences

ICUIMC '11: Proceedings of the 5th International Conference on Ubiquitous Information Management and Communication

February 2011

959 pages

ISBN:9781450305716

DOI:10.1145/1968613

General Chairs:
Suk-Han Lee
Sungkyunkwan University, Korea
,
Lajos Hanzo
University of Southampton
,
Program Chairs:
Min Young Chung
Sungkyunkwan University, Korea
,
Sang-Won Lee
Sungkyunkwan University, Korea
,
Kwangsu Cho
University of Missouri

Copyright © 2011 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

SIGAPP: ACM Special Interest Group on Applied Computing
SIGKDD: ACM Special Interest Group on Knowledge Discovery in Data
SKKU: SUNGKYUNKWAN UNIVERSITY

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 21 February 2011

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ICUIMC '11

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ICUIMC '11: The 5th International Conference on Ubiquitous Information Management and Communication

February 21 - 23, 2011

Seoul, Korea

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ICUIMC '11 Paper Acceptance Rate 135 of 534 submissions, 25%;

Overall Acceptance Rate 251 of 941 submissions, 27%

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Cited By

Sun XYan KZhou X(2020)Fault Detection and Diagnosis of Chillers with S&D Convolutional Neural Network2020 International Conferences on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData) and IEEE Congress on Cybermatics (Cybermatics)10.1109/iThings-GreenCom-CPSCom-SmartData-Cybermatics50389.2020.00141(829-836)Online publication date: Nov-2020
https://doi.org/10.1109/iThings-GreenCom-CPSCom-SmartData-Cybermatics50389.2020.00141
Yuan YHuang JMa XYan K(2020)Children's Drawing Psychological Analysis using Shallow Convolutional Neural Network2020 International Conferences on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData) and IEEE Congress on Cybermatics (Cybermatics)10.1109/iThings-GreenCom-CPSCom-SmartData-Cybermatics50389.2020.00120(692-698)Online publication date: Nov-2020
https://doi.org/10.1109/iThings-GreenCom-CPSCom-SmartData-Cybermatics50389.2020.00120
Zhou XJin Q(2017)A heuristic approach to discovering user correlations from organized social stream dataMultimedia Tools and Applications10.1007/s11042-014-2153-576:9(11487-11507)Online publication date: 1-May-2017
https://dl.acm.org/doi/10.1007/s11042-014-2153-5
Wu BZhou XJin Q(2015)Participatory information search and recommendation based on social roles and networksMultimedia Tools and Applications10.1007/s11042-013-1849-274:14(5173-5188)Online publication date: 1-Jul-2015
https://dl.acm.org/doi/10.1007/s11042-013-1849-2
Zhou XWu BJin QNishimura SPan JZheng WMa J(2014)Social Stream Organization Based on User Role Analysis for Participatory Information RecommendationProceedings of the 2014 7th International Conference on Ubi-Media Computing and Workshops10.1109/U-MEDIA.2014.57(105-110)Online publication date: 12-Jul-2014
https://dl.acm.org/doi/10.1109/U-MEDIA.2014.57
Zhou XYen NJin QShih T(2013)Enriching user search experience by mining social streams with heuristic stones and associative ripplesMultimedia Tools and Applications10.1007/s11042-012-1069-163:1(129-144)Online publication date: 1-Mar-2013
https://dl.acm.org/doi/10.1007/s11042-012-1069-1
Lee CCroft WKim JAdar ETeevan JAgichtein EMaarek Y(2012)Evaluating search in personal social media collectionsProceedings of the fifth ACM international conference on Web search and data mining10.1145/2124295.2124375(683-692)Online publication date: 8-Feb-2012
https://dl.acm.org/doi/10.1145/2124295.2124375
Chen HZhou XJin Q(2012)Socialized ubiquitous personal studyJournal of Computer and System Sciences10.1016/j.jcss.2011.10.02078:6(1775-1792)Online publication date: 1-Nov-2012
https://dl.acm.org/doi/10.1016/j.jcss.2011.10.020
Zhou XJin Q(2012)User correlation discovery and dynamical profiling based on social streamsProceedings of the 8th international conference on Active Media Technology10.1007/978-3-642-35236-2_6(53-62)Online publication date: 4-Dec-2012
https://dl.acm.org/doi/10.1007/978-3-642-35236-2_6
Zhou XChen JJin QShih T(2012)Learning activity sharing and individualized recommendation based on dynamical correlation discoveryProceedings of the 11th international conference on Advances in Web-Based Learning10.1007/978-3-642-33642-3_21(200-206)Online publication date: 2-Sep-2012
https://dl.acm.org/doi/10.1007/978-3-642-33642-3_21
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