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BEGIN:VEVENT
UID:DSC-6519
DTSTART;TZID=Europe/Berlin:20140110T130000
SEQUENCE:1389340463
TRANSP:OPAQUE
DTEND;TZID=Europe/Berlin:20140110T140000
URL:https://dresden-science-calendar.de/calendar/de/detail/6519
LOCATION:TUD Andreas-Pfitzmann-Bau\, Nöthnitzer Straße 4601069 Dresden
SUMMARY:Muthmann: Community based Question Answer Detection
CLASS:PUBLIC
DESCRIPTION:Speaker: Dipl.-Medieninf. Klemens Muthmann\nInstitute of Speake
 r: Institut für Systemarchitektur\, Lehrstuhl Rechnernetze\nTopics:\nInfo
 rmatik\n Location:\n  Name: TUD Andreas-Pfitzmann-Bau (INF 1004  (Ratssaal
 ))\n  Street: Nöthnitzer Straße 46\n  City: 01069 Dresden\n  Phone: \n  
 Fax: \nDescription: Each day millions of people ask questions and search a
 nswers on the World Wide Web. Due to this\, the Internet has grown to a wo
 rld wide database of questions and answers\, accessible to almost everyone
 . Since this database is so huge\, it is hard to find out if a question ha
 s been answered or even asked before. This leads to users asking the same 
 questions again and again\, producing a vicious circle of new content\, wh
 ich hides the important information.    One famous platform for questions 
 and answers are Web forums\, also known as discussion boards. They present
  discussions as item streams\, where each item contains the contribution o
 f one author. These contributions contain questions and answers in human r
 eadable form. People use search engines to search information on such plat
 forms. However\, current search engines are not optimized to highlight ind
 ividual questions and answers\, to show which  questions are asked often a
 nd which ones are already answered.    To close this gap\, this thesis int
 roduces the Effingo system. The Effingo system is intended to extract foru
 ms from around the Web and find question and answer items. It also needs t
 o link equal questions and aggregate associated answers. That way it is po
 ssible to find out if a question was asked before and if it is already ans
 wered. Based on this information one  can derive the most urgent questions
  in the system\, which are new and which are discussed and answered freque
 ntly. As a result\, users are prevented from creating useless discussions\
 , reducing the server load and information overload for further searches. 
    The research areas the Effingo system taps are forum data extraction\, 
 to manage a database of forum posts as large as possible. Furthermore it u
 ses question answer detection to find out which forum items are questions 
 and which are answers and\, finally\, topic detection to aggregate questio
 ns on the same topic\, as well as finding which answers are duplicates. Th
 ese areas are either extended by Effingo\, using forum specific features s
 uch as the user graph\, forum item relations and forum link structure\, or
  adapted to cope with the specific problems posed by user generated conten
 t. Such problems arise from poorly written and very short texts\, as well 
 as hidden or distributed information.
DTSTAMP:20260624T203915Z
CREATED:20131219T080215Z
LAST-MODIFIED:20140110T075423Z
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