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Logo: Institut für Verteilte Systeme - Fachgebiet Wissensbasierte Systeme (KBS)
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Web Science

Important Infos

Please select a time slot for your oral exam!!  https://doodle.com/kuqwennt5kau2ss9


https://doodle.com/kuqwennt5kau2ss9

Overview

Course start: 15.04.2014, 15.00-16:30, Multimedia-Hörsaal (3703 - 023)

Teaching Team

  • Responsible Professor: Prof. Dr. techn. Wolfgang Nejdl
  • Assistance: Sergej Zerr (Home Page), Xiaofei Zhu  (Homepage)
  • NOTE: Please put "WebScienceCourse" into the subject line when writing an email
  • LINK TO Web Science 2013  

Schedule

  • Lecture: Tuesdays 15:00 - 16:30
  • Room: Multimedia-Hörsaal (3703 - 023), Appelstraße 4, 30167 Hannover
  • Live - Transmition:  https://webconf.vc.dfn.de/websciencecourse (please ask Sergej or Xiaofei for the password to access this virtual room)
  • Please select a date for your oral presentation here(up to two students may select the same date): doodle

Oral Exam

The oral exam is composed of two parts:

  1. Detailed questions on the papers presented by the student during the course. The presentation of a paper is compulsory!
  2. More general questions on other papers of the same topic, and some on other topics. As a guideline you should be able to answer the following questions:

    • What is the problem addressed in the paper?
    • How does the solution look like?
    • How is it evaluated?

    Schedule

    Send an email to Sergej, or Xiaofei to book a time slot for the oral exam. Please notify if the date is not appropriate anymore for you!

    Location

    2. OG, Appelstraße 4, 30167 Hannover. Please ring the bell to enter, and wait in the waiting room in the middle of the hall.

    Slide Template

    Please use the provided slide template for your presentation. (powerpoint / latex)

Topics for Student Paper Presentation

Below are the topics of Web Science which will be addressed in the course. Each student will have to pick two papers that she/he will present to the other students in the second part of the course. Details about how to subscribe will follow.

Hints:

Here we collected hints helping you to prepare a good presentation.

Here a standard PowerPoint template for the presentation, here the Latex version. This template is not mandatory! Please feel free to use your own designs. Here is a good example for a student work from last year.

Subscription

Send a mail to Sergej or Xiaofei with the following details:

  • At least 2 papers that you wish to present.
  • If there is a laps of time during the semester lecture period when you absolutely cannot present, please mention this in the mail.
  • If there is a period when you would preferably present, please also mention this.

Note that we try to take into account the following criteria when attributing the one paper which students will present:

  • Papers will be assigned to students as soon as possible according to the first come first served policy.
  • The exact presentation date will be definitely fixed as soon as 2 papers about a same topic has been attributed.
  • Presentations about a same topic should take place the same day.
  • As far as possible a similar number of paper per topic would be presented.
  • Each topic should at least have one paper presented.

Available Topic Papers

Below are papers available to you for presenting, grouped by topics. Papers already attributed to a student are marked as such. Papers from topics of which two papers are already attributed are no more available for presentation. 

 

1. Mining News Collections

  • Jure Leskovec, Lars Backstrom, Jon M. Kleinberg: Meme-tracking and the dynamics of the news cycle. KDD 2009: 497-506 (pdf) [selected by Markus]
  • Kira Radinsky, Sagie Davidovich, Shaul Markovitch: Learning causality for news events prediction. WWW 2012: 909-918 (pdf) [selected by Markus]
  • Di Wu, Yiping Ke, Jeffrey Xu Yu, Zheng Liu: Detecting Priming News Events Cornell University Library 2012 (pdf) [selected by Imene]
  • Kira Radinsky, Eric Horvitz: Mining the Web to Predict Future Events. WISDM 2013 (pdf) [selected by Imene]

2. Query Recommendation

  • Makoto P. Kato, Tetsuya Sakai, Katsumi Tanaka: Structured query suggestion for specialization and parallel movement: effect on search behaviors. WWW 2012: 389-398 (pdf) [selected by Oswald]
  • Yang Liu, Ruihua Song, Yu Chen, Jian-Yun Nie, Ji-Rong Wen: Adaptive query suggestion for difficult queries. SIGIR 2012: 15-24 (pdf) [selected by Oswald]
  • Umut Ozertem, Olivier Chapelle, Pinar Donmez, Emre Velipasaoglu: Learning to Suggest: A Machine Learning Framework for Ranking Query Suggestions. SIGIR 2012: 25-34  (pdf)
  • Hossein Vahabi, Margareta Ackerman, David Loker, Ricardo Baeza-Yates, Alejandro Lopez-Ortiz: Orthogonal query recommendation. RecSys 2013: 33-40 (pdf)
  • Eugene Kharitonovyz,Craig Macdonaldz,Pavel Serdyukovy,Iadh Ounisz: User Model-based Metrics for Offline Query Suggestion Evaluation. SIGIR 2013: 633-642 (pdf)

3. Foundations for Temporal Retrieval, Exploration and Analytics in Web Archives

  • Robert Sanderson: Global web archive integration with memento. JCDL 2012:379-380 (pdf)
  • Siân E. Lindley, Catherine C. Marshall, et al.: Rethinking the web as a personal archive. WWW 2013: 749-760 (pdf)
  • Salaheldeen, H.; Nelson, M. L.: Losing My Revolution: How Many Resources Shared on Social Media Have Been Lost? TPDL 2012: 125-137 (pdf) [selected by Subhash]
  • Alonso, O.; Strötgen, J.; Baeza-Yates, R.; Gertz, M.: Temporal information retrieval: Challenges and opportunities. TWAW 2011: 1-8 (pdf) [selected by Subhash]

4. Temporal Web Dynamics and Implications from Search Perspective

  • Kira Radinsky, Krysta Svore, Susan Dumais, Jaime Teevan, Alex Bocharov, Eric Horvitz: Modeling and predicting behavioral dynamics on the web. WWW 2012: 599-608 (pdf)
  • Milad Shokouhi, Kira Radinsky: Time-sensitive query auto-completion. SIGIR 2012:601-610 (pdf)
  • Tu Ngoc Nguyen and Nattiya Kanhabua: Leveraging Dynamic Query Subtopics for Time-aware Search Result Diversification. ECIR 2014: 222-234 (pdf)
  • Maria-Hendrike Peetz, Edgar Meij, Maarten de Rijke: Using temporal bursts for query modeling. Information Retrieval 2014 17(1):74-108(pdf)

5. Social Networking

  • Jeffrey Travers, Stanley Milgram: An experimental study of the small world problem.Sociometry, 1969, 32(4): 425-443. (pdf)  [selected by Suo]
  • Jure Leskovec, Eric Horvitz: Planetary-scale views on a large instant-messaging network. WWW 2008: 915-924. (pdf) [selected by Suo]
  • Jure Leskovec, Daniel Huttenlocher, Jon Kleinberg: Signed networks in social media. CHI 2010: 1361-1370. (pdf
  • Jérôme Kunegis, Andreas Lommatzsch, Christian Bauckhage: The slashdot zoo: mining a social network with negative edges. WWW 2009: 741-750. (pdf)

6. Mining the Social Web

  • Haewoon Kwak, Changhyun Lee, Hosung Park, and Sue Moon: What is Twitter, a social network or a news media?. WWW 2010:591-600 (pdf) [selected by Jingzhe Ding]
  • M.D. Conover, J. Ratkiewicz, M. Francisco, B. Goncalves, A. Flammini, and F. Menczer. Political polarization on twitter. In Proc. 5th Intl. Conference on Weblogs and Social Media, 2011. (pdf) [selected by Jingzhe Ding]
  • Ricardo Kawase, Bernardo Pereira Nunes, Eelco Herder, Wolfgang Nejdl, and Marco Antonio Casanova. Who wants to get fired? CHI, April 27- May 2 2013.  (pdf[selected by Cheng Li]
  • Marco Pennacchiotti and Ana-Maria Popescu. Democrats, republicans and starbucks affcionados: user classification in twitter. In Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining, KDD 2011: 430-438 (pdf[selected by Cheng Li]

7. Topic Modelling

  • Jonathan Chang, Jordan Boyd-Graber, et al.: Reading Tea Leaves: How Humans Interpret Topic Models. NIPS 2009 (pdf)(alternative pdf)
  • David Mimno, Hanna M. Wallach, et al.: Optimizing Semantic Coherence in Topic Models. EMNLP 2011: 262-272 (pdf)
  • Jey Han Lau, Karl Grieser, et al.:Automatic Labelling of Topic Models. HLT 2011: 1536-1545 (pdf)
  • Qiaozhu Mei, Xuehua Shen, ChengXiang Zhai:Automatic Labeling of Multinomial Topic Models. KDD 2007: 490-499 (pdf)

8. Semantic Web: Extracting and Mining Structured Data from Unstructured Content

  • Alessio Palmero Aprosio, Claudio Giuliano, Alberto Lavelli: Automatic Expansion of DBpedia Exploiting Wikipedia Cross-Language Information. ESWC 2013:397-411 (pdf) [selected by Sascha Ortmann]
  • Dimitris Kontokostas, Patrick Westphal, et al.: Test-driven Evaluation of Linked Data Quality. WWW 2014: 747-757 (pdf)
  • Daniel M. Herzig, Peter Mika, Roi Blanco, Thanh Tran: Federated Entity Search using On-The-Fly Consolidation.  ISWC 2013: 167-183 (pdf)
  • Fabian M. Suchanek, Gjergji Kasneci, Gerhard Weikum: YAGO: A Core of Semantic Knowledge Unifying WordNet and Wikipedia. WWW 2007: 697-706 (pdf) [selected by Sascha Ortmann]

9. Long-Term Preservation of architectural knowledge

  • D. Quercia, J. P. Pesce, V. Almeida, and J. Crowcroft: Psychological maps 2.0: A web engagement enterprise starting in london. WWW 2013: 1065-1076 (pdf)
  • N. Lathia, D. Quercia, and J. Crowcroft: The hidden image of the city: sensing community well-being from urban mobility. Pervasive Computing 2012: 91–98 (pdf)
  • D. Quercia: Urban: crowdsourcing for the good of london. WWW 2013:591-592 (pdf)
  • Yu Zheng, Yanchi Liu, Jing Yuan, Xing Xie: Urban Computing with Taxicabs, UbiComp 2011: 89-98 (pdf)

Detailed Schedule  

15.04.2014

Lecture

  • Introduction to Web Sciences(Prof.Dr. Wolfgang Nejdl)
  • Slides PPT
  • Mining News Collections (Avishek Anand)
  • Slides PPT 

 

22.04.2014

Lecture

 

29.04.2014

Lecture

  • Foundations for Temporal Retrieval, Exploration and Analytics in Web Archives (Prof.Dr. Wolfgang Nejdl)
  • Slides PPT 

 

06.05.2014

Lecture

  • Temporal Web Dynamics and Implications from Search Perspective (Nattyia Kanhabua)
  • Slides PPT

 

13.05.2014

Lecture

 

20.05.2014

Lecture

  • Semantic Web: Extracting and Mining Structured Data from Unstructured Content (Besnik Fetahu 
  • Slides PPT

 

27.05.2014

Lecture

 

03.06.2014

Lecture

 

17.06.2014

Lecture

  • Long-Term Preservation of architectural knowledge (Ujwal Gadiraju) 
  • Slides PPT

Topics and papers selected by students:

 

Social Network 

Qiang Suo (Presented 24 July)

  • Jeffrey Travers, Stanley Milgram: An experimental study of the small world problem.Sociometry, 1969, 32(4): 425-443.
  • Jure Leskovec, Eric Horvitz: Planetary-scale views on a large instant-messaging network. WWW 2008: 915-924.

Mining news collections

  • Markus Rocicki

    • Jure Leskovec, Lars Backstrom, Jon M. Kleinberg: Meme-tracking and the dynamics of the news cycle. KDD 2009: 497-506
    • Kira Radinsky, Sagie Davidovich, Shaul Markovitch: Learning causality for news events prediction. WWW 2012: 909-918

  • Imene Tighane

    • Detecting Priming News Events : Di Wu, Yiping Ke, Jeffrey Xu Yu, Zheng Liu
    • Mining the Web to Predict Future Events : Kira Radinsky, Eric Horvitz

 Query Recommendation

  • Oswald Yinyeh

    • Umut Ozertem, Olivier Chapelle, Pinar Donmez, Emre Velipasaoglu: Learning to Suggest: A Machine Learning Framework for Ranking Query Suggestions. SIGIR 2012: 25-34
    • Yang Liu, Ruihua Song, Yu Chen, Jian-Yun Nie, Ji-Rong Wen: Adaptive query suggestion for difficult queries. SIGIR 2012: 15-24
    •  

 Mining Social Web

  • Cheng LI

    • Marco Pennacchiotti and Ana-Maria Popescu. Democrats, republicans and starbucks affcionados: user classification in twitter.
    • Ricardo Kawase, Bernardo Pereira Nunes, Eelco Herder, Wolfgang Nejdl, and Marco Antonio Casanova. Who wants to get fired?

  • Jingzhe Ding

    • Haewoon Kwak, Changhyun Lee, Hosung Park, and Sue Moon: What is Twitter, a social network or a news media?.  
    • M.D. Conover, J. Ratkiewicz, M. Francisco, B. Goncalves, A. Flammini, and F. Menczer. Political polarization on twitter.

Foundations for Temporal Retrieval, Exploration and Analytics in Web Archives 

  • Subhash Chandra Pujari

    • Salaheldeen, H.; Nelson, M. L.: Losing My Revolution: How Many Resources Shared on Social Media Have Been Lost? TPDL 2012: 125-137
    • Alonso, O.; Strötgen, J.; Baeza-Yates, R.; Gertz, M.: Temporal information retrieval: Challenges and opportunities. TWAW 2011: 1-8

Foundations for Temporal Retrieval, Exploration and Analytics in Web Archives 

  • Mohammad Wazed Ali

    • Robert Sanderson: Global web archive integration with memento. JCDL 2012:379-380
    • Siân E. Lindley, Catherine C. Marshall, et al.: Rethinking the web as a personal archive. WWW 2013: 749-760

Semantic Web: Extracting and Mining Structured Data from Unstructured Content

Long-Term Preservation of architectural knowledge

  • Fabian Pflug

    • N. Lathia, D. Quercia, and J. Crowcroft: The hidden image of the city: sensing community well-being from urban mobility. Pervasive Computing 2012: 91–98
    • Yu Zheng, Yanchi Liu, Jing Yuan, Xing Xie: Urban Computing with Taxicabs, UbiComp 2011: 89-98

Final Oral Exam

TBD