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1st International Workshop on Search and Mining Terrorist Online Content & Advances in Data Science for Cyber Security and Risk on the Web

Theodora Tsikrika, Babak Akhgar, Vasilis Katos, Stefanos Vrochidis, Pete Burnap, Matthew L. Williams
2017 Proceedings of the Tenth ACM International Conference on Web Search and Data Mining - WSDM '17  
The workshop programme includes refereed papers, invited talks and a panel discussion for better understanding the current landscape, as well as the future of data mining for detecting cyber deviance.  ...  The deliberate misuse of technical infrastructure (including the Web and social media) for cyber deviant and cybercriminal behaviour, ranging from the spreading of extremist and terrorismrelated material  ...  WSDM 2017 , 2017 February 06-10, 2017, Cambridge, United Kingdom ACM 978-1-4503-4675-7/17/02. http://dx.doi.org/10.1145/3018661.3022760  ... 
doi:10.1145/3018661.3022760 dblp:conf/wsdm/TsikrikaAKVBW17 fatcat:v665ayq5ivf3bephgxrb2enkfe

Lightweight Multilingual Entity Extraction and Linking

Aasish Pappu, Roi Blanco, Yashar Mehdad, Amanda Stent, Kapil Thadani
2017 Proceedings of the Tenth ACM International Conference on Web Search and Data Mining - WSDM '17  
Our system achieves state-of-the-art performance on tac kbp 2013 multilingual data and on English aida-conll data.  ...  The contributions of this paper are three-fold: 1) Lightweight named entity recognition with competitive accuracy; 2) Candidate entity retrieval that uses search clicklog data and entity embeddings to  ...  WSDM 2017 , 2017 February 06-10, 2017, Cambridge, United Kingdom c 2017 ACM.  ... 
doi:10.1145/3018661.3018724 dblp:conf/wsdm/PappuBMST17 fatcat:brp5m4y6g5bjli7snvq6pzinna

Learning from User Interactions in Personal Search via Attribute Parameterization

Michael Bendersky, Xuanhui Wang, Donald Metzler, Marc Najork
2017 Proceedings of the Tenth ACM International Conference on Web Search and Data Mining - WSDM '17  
We consider the problem of discovering local events on the web, where events are entities extracted from webpages.  ...  (a) the challenge of feature sparseness and noisiness, and (b) the semantic mismatch problem in a self-contained and principled manner.  ...  WSDM 2017 February 06-10, 2017, Cambridge, United Kingdom c 2017 Copyright held by the owner/author(s). ACM ISBN 978-1-4503-4675-7/17/02. DOI: http://dx.doi.org/10.1145/3018661.3018712 .  ... 
doi:10.1145/3018661.3018712 dblp:conf/wsdm/BenderskyWMN17 fatcat:vkfkqj4spjdtpe2cuuhm62kl5y

Anticipating Information Needs Based on Check-in Activity

Jan R. Benetka, Krisztian Balog, Kjetil Nørvåg
2017 Proceedings of the Tenth ACM International Conference on Web Search and Data Mining - WSDM '17  
Using a combination of historical check-in data and manual assessments collected via crowdsourcing, we show experimentally the effectiveness of our approach.  ...  In this work we address the development of a smart personal assistant that is capable of anticipating a user's information needs based on a novel type of context: the person's activity inferred from her  ...  WSDM 2017 , 2017 February 06 -10, 2017, Cambridge, United Kingdom © 2017 Copyright held by the owner/author(s). Publication rights licensed to ACM.  ... 
doi:10.1145/3018661.3018679 dblp:conf/wsdm/BenetkaBN17 fatcat:wxs56cdvszhm3nbo7znxyzofwe

Recurrent Recommender Networks

Chao-Yuan Wu, Amr Ahmed, Alex Beutel, Alexander J. Smola, How Jing
2017 Proceedings of the Tenth ACM International Conference on Web Search and Data Mining - WSDM '17  
On multiple real-world datasets, our model offers excellent prediction accuracy and it is very compact, since we need not learn latent state but rather just the state transition function.  ...  Recommender systems traditionally assume that user profiles and movie attributes are static.  ...  Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation, or other funding  ... 
doi:10.1145/3018661.3018689 dblp:conf/wsdm/WuABSJ17 fatcat:qggq72dolva35fvdudqtdepbui

Task and Model Agnostic Adversarial Attack on Graph Neural Networks [article]

Kartik Sharma, Samidha Verma, Sourav Medya, Sayan Ranu, Arnab Bhattacharya
2021 arXiv   pre-print
Specifically, we formulate the problem of task and model agnostic evasion attacks where adversaries modify the test graph to affect the performance of any unknown downstream task.  ...  Extensive experiments on real datasets show that, on average, GRAND is up to 50% more effective than state of the art techniques, while being more than 100 times faster.  ...  ing, WSDM 2017, Cambridge, United Kingdom, February Semi-supervised classification with graph convolutional 6-10, 2017, pages 601–610. ACM, 2017. networks.  ... 
arXiv:2112.13267v1 fatcat:ixldolkfkfctrbk33akaorjqsu

Learning Parametric Models for Context-Aware Query Auto-Completion via Hawkes Processes

Liangda Li, Hongbo Deng, Jianhui Chen, Yi Chang
2017 Proceedings of the Tenth ACM International Conference on Web Search and Data Mining - WSDM '17  
The proposed method is evaluated on two realworld benchmark data in comparison with state-of-art methods, and the obtained experiments clearly demonstrate their effectiveness.  ...  We propose a novel Hawkes process based QAC algorithm, comprehensively taking into account the context, temporal, and position of the clicked recommended query completions (a type of user behavior data  ...  Meanwhile, we plan to investigate alternative models that can be applied to other search tasks. WSDM 2017 , 2017 February 06-10, 2017, Cambridge, United Kingdom © 2017 ACM.  ... 
doi:10.1145/3018661.3018698 dblp:conf/wsdm/LiDCC17 fatcat:cdvbryimhjg7xm3vyoz2mbiom4

Partitioning and Segment Organization Strategies for Real-Time Selective Search on Document Streams

Yulu Wang, Jimmy Lin
2017 Proceedings of the Tenth ACM International Conference on Web Search and Data Mining - WSDM '17  
Previous work on web collections has shown that it is possible to retain high-quality results while considering only a small fraction of the collection.  ...  In this work, we consider the novel formulation of selective search on document streams (specifically, tweets), where partitioning must be performed incrementally.  ...  This research was supported by the U.S. National Science Foundation (NSF) under IIS-1218043 and CNS-1405688, and the Natural Sciences and Engineering Research Council of Canada (NSERC).  ... 
doi:10.1145/3018661.3018727 dblp:conf/wsdm/WangL17 fatcat:5vi2rnswxrdnhk7733stxs2ofi

Beyond the Words

Honghao Wei, Fuzheng Zhang, Nicholas Jing Yuan, Chuan Cao, Hao Fu, Xing Xie, Yong Rui, Wei-Ying Ma
2017 Proceedings of the Tenth ACM International Conference on Web Search and Data Mining - WSDM '17  
We evaluate our methods with extensive experiments based on a real-world data covering both personality survey results and social media usage from thousands of volunteers.  ...  However, except for single language features, a less researched direction is how to leverage the heterogeneous information on social media to have a better understanding of user personality.  ...  WSDM 2017, February 06-10, 2017, Cambridge, United Kingdom c 2017 ACM.  ... 
doi:10.1145/3018661.3018717 dblp:conf/wsdm/WeiZYCFXRM17 fatcat:q7cyxl6nwvexvk4n3fp7xgjtpe

Raising Graphs From Randomness to Reveal Information Networks

Róbert Pálovics, András A. Benczúr
2017 Proceedings of the Tenth ACM International Conference on Web Search and Data Mining - WSDM '17  
Parameters of the average degree growth and the power-law degree distribution exponent functions depend on the ratio of the network growth exponent parameters.  ...  Specifically, we connect the growth of the average degree to the decreasing exponent of the power-law degree distribution. Prior to our work, only one of the two cases were handled.  ...  WSDM 2017 , 2017 February 06-10, 2017, Cambridge, United Kingdom c 2017 ACM.  ... 
doi:10.1145/3018661.3018664 dblp:conf/wsdm/PalovicsB17 fatcat:2ko3jplforbktm5dk5koxzkgwu

Algorithms for Active Classifier Selection

Paul N. Bennett, David M. Chickering, Christopher Meek, Xiaojin Zhu
2017 Proceedings of the Tenth ACM International Conference on Web Search and Data Mining - WSDM '17  
Search engines, for example, use query classifiers to trigger specialized "instant answer" experiences where information satisfying the user query is shown directly on the result page, and email applications  ...  We develop adaptive model-selection algorithms to identify, using as few samples as possible, the best classifier from among a set of (precision) qualifying classifiers.  ...  WSDM 2017, February 06-10, 2017, Cambridge, United Kingdom c 2017 ACM.  ... 
doi:10.1145/3018661.3018730 dblp:conf/wsdm/BennettCMZ17 fatcat:ged2kupzc5bhhdmyqezeh5s6ii

Temporally Factorized Network Modeling for Evolutionary Network Analysis

Wenchao Yu, Charu C. Aggarwal, Wei Wang
2017 Proceedings of the Tenth ACM International Conference on Web Search and Data Mining - WSDM '17  
We present a number of experimental results on a number of temporal data sets showing the effectiveness of the approach.  ...  This is because, unlike multidimensional data, the edges in the network reflect interactions among nodes, and it is difficult to independently model the edge as a function of time, without taking into  ...  The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Army Research Laboratory  ... 
doi:10.1145/3018661.3018669 pmid:28626845 pmcid:PMC5470848 dblp:conf/wsdm/YuA017 fatcat:suhnuigswzfzpl2bjrm6ulbmsu

Does Document Relevance Affect the Searcher's Perception of Time?

Cheng Luo, Yiqun Liu, Tetsuya Sakai, Ke Zhou, Fan Zhang, Xue Li, Shaoping Ma
2017 Proceedings of the Tenth ACM International Conference on Web Search and Data Mining - WSDM '17  
factors that have impacts on search users' perception of time.  ...  By further examining the impact of other factors, we demonstrate that the effect on relevant documents can be also influenced by individuals and tasks. (3) We conduct a preliminary experiment in which  ...  This work was supported by Natural Science Foundation (61622208, 61532011, 61472206) of China and National Key Basic Research Program (2015CB358700).  ... 
doi:10.1145/3018661.3018694 dblp:conf/wsdm/LuoLSZZLM17 fatcat:ddlxfqtw55a4pit6epj2mrb4yq

Constructing and Embedding Abstract Event Causality Networks from Text Snippets

Sendong Zhao, Quan Wang, Sean Massung, Bing Qin, Ting Liu, Bin Wang, ChengXiang Zhai
2017 Proceedings of the Tenth ACM International Conference on Web Search and Data Mining - WSDM '17  
In this paper, we formally define the problem of representing and leveraging abstract event causality to power downstream applications.  ...  Given the causality network and the learned embeddings, our model can be applied to a wide range of applications such as event prediction, event clustering and stock market movement prediction.  ...  This work was done while the author was visiting Institute of Information Engineering Chinese Academy of Sciences and University of Illinois at Urbana-Champaign.  ... 
doi:10.1145/3018661.3018707 dblp:conf/wsdm/ZhaoWMQLWZ17 fatcat:4t255l3p5ndglefvp7zmunzrsy

Evolution of Ego-networks in Social Media with Link Recommendations

Luca Maria Aiello, Nicola Barbieri
2017 Proceedings of the Tenth ACM International Conference on Web Search and Data Mining - WSDM '17  
To shed light on this matter, we analyze the complete temporal evolution of 170M ego-networks extracted from Flickr and Tumblr, comparing links that are created spontaneously with those that have been  ...  We find that the evolution of ego-networks is bursty, community-driven, and characterized by subsequent phases of explosive diameter increase, slight shrinking, and stabilization.  ...  WSDM 2017 , 2017 February 06 -10, 2017, Cambridge, United Kingdom c 2017 Copyright held by the owner/author(s). Publication rights licensed to ACM.  ... 
doi:10.1145/3018661.3018733 dblp:conf/wsdm/AielloB17 fatcat:p5rml756fzg45no5ew2na7vayy
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