So done... (Huan's talk should gel well with the social networks discussion we started in the class)
rao
rao
---------- Forwarded message ----------
From: Farooq Khera <fkhera@asu.edu>
Date: Fri, Sep 26, 2008 at 9:21 AM
Subject: Fwd: Faculty Seminar Series: Today's presentation by Prof. Huan Liu ( 3 PM at BYAC 110): ORG-ENG-CSE_Online_Com
To: Subbarao Kambhampati <rao@asu.edu>
From: Farooq Khera <fkhera@asu.edu>
Date: Fri, Sep 26, 2008 at 9:21 AM
Subject: Fwd: Faculty Seminar Series: Today's presentation by Prof. Huan Liu ( 3 PM at BYAC 110): ORG-ENG-CSE_Online_Com
To: Subbarao Kambhampati <rao@asu.edu>
This lecture sounds really interesting - perhaps you can forward to class :-D
---------- Forwarded message ----------
From: Chitta Baral <chitta.baral@asu.edu>
Date: Fri, Sep 26, 2008 at 7:00 AM
Subject: Faculty Seminar Series: Today's presentation by Prof. Huan Liu ( 3 PM at BYAC 110): ORG-ENG-CSE_Online_Com
To: "ORG-ENG-CSE_Online_Com"
(NOTE: Location changed to BYAC 110 as it became available. Rest of the semester we will be in BYAC 110.)
Time & Date: September 26th, 3 PM - 4:15 PM
(Coffee and cookies from 2:45 PM)
Location: BYAC 110
Title: Data Mining and Social Computing: Moving Forward in Interdisciplinary Research
Speaker: Prof. Huan Liu
Abstract:
Data mining finds actionable nuggets from massive data. Social computing is concerned with the study of social behaviors and social context based on computational systems including social media on the Web. Challenges from data are numerous. Two of the common ones are of high dimensionality and of exceedingly large numbers of data points.
Feature selection is one effective means to tackle data of high dimensionality. It differs from feature extraction in that it selects a relevant subset of original features, which is often required by domain experts in many real-world applications. With the pervasive use of social media such as wiki, social networking sites, and blogging, more and more users can conveniently express themselves in endless
ways. It is imperative to develop novel approaches to help understand what's happening and how to tap into the increasing volume of data generated from social media. In this talk, we first present an overview of our lab research activities in data mining and social computing, then elaborate two research lines on feature selection and
on identifying influential bloggers, and conclude with some
representative challenging research issues we are currently working on such as multi-source feature selection, finding "familiar strangers" in the blogosphere, and trust in Health 2.0.
=== Upcoming Seminars in October ===
3rd October: Prof. Dijiang Huang (BYAC 110)
10th October: Prof. Winslow Burleson (BYAC 110)
17th October: Prof. Hari Sundaram (BYAC 110)
24th October: Prof. Arunabha Sen (BYAC 110)
31st October: Prof. Yi Chen (BYAC 110)
From: Chitta Baral <chitta.baral@asu.edu>
Date: Fri, Sep 26, 2008 at 7:00 AM
Subject: Faculty Seminar Series: Today's presentation by Prof. Huan Liu ( 3 PM at BYAC 110): ORG-ENG-CSE_Online_Com
To: "ORG-ENG-CSE_Online_Com"
(NOTE: Location changed to BYAC 110 as it became available. Rest of the semester we will be in BYAC 110.)
Time & Date: September 26th, 3 PM - 4:15 PM
(Coffee and cookies from 2:45 PM)
Location: BYAC 110
Title: Data Mining and Social Computing: Moving Forward in Interdisciplinary Research
Speaker: Prof. Huan Liu
Abstract:
Data mining finds actionable nuggets from massive data. Social computing is concerned with the study of social behaviors and social context based on computational systems including social media on the Web. Challenges from data are numerous. Two of the common ones are of high dimensionality and of exceedingly large numbers of data points.
Feature selection is one effective means to tackle data of high dimensionality. It differs from feature extraction in that it selects a relevant subset of original features, which is often required by domain experts in many real-world applications. With the pervasive use of social media such as wiki, social networking sites, and blogging, more and more users can conveniently express themselves in endless
ways. It is imperative to develop novel approaches to help understand what's happening and how to tap into the increasing volume of data generated from social media. In this talk, we first present an overview of our lab research activities in data mining and social computing, then elaborate two research lines on feature selection and
on identifying influential bloggers, and conclude with some
representative challenging research issues we are currently working on such as multi-source feature selection, finding "familiar strangers" in the blogosphere, and trust in Health 2.0.
=== Upcoming Seminars in October ===
3rd October: Prof. Dijiang Huang (BYAC 110)
10th October: Prof. Winslow Burleson (BYAC 110)
17th October: Prof. Hari Sundaram (BYAC 110)
24th October: Prof. Arunabha Sen (BYAC 110)
31st October: Prof. Yi Chen (BYAC 110)
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