Detecting Promotion Campaigns in Query Auto Completion
ACM International Conference on Information and Knowledge Management(2016)
摘要
Query Auto Completion (QAC) aims to provide possible
suggestions to Web search users from the moment they start
entering a query, which is thought to reduce their physical and
cognitive efforts in query formulation. However, the QAC has
been misused by malicious users, being transformed into a new
form of promotion campaign. These malicious users attack the
search engines to replace legitimate auto-completion candidate
suggestions with manipulated contents. Through this way, they
provide a new malicious advertising service to promote their
customers’ products or services in QAC. To our best knowledge,
we are among the first to investigate this new type of Promotion
Campaign in QAC (PCQ). Firstly, we look into the causes of PCQ
based on practical commercial search query logs. We found that
various queries containing certain promotion intents are submitted
multiple times to search engines to promote their rankings in QAC.
Secondly, an effective promotion query detection framework is
proposed by promotion intent propagation on query-user bipartite
graph, which takes into account the behavioral characteristics of
promotion campaigns. Finally, we extend the query detection
framework to promotion target detection to identify the consistent
promotion target which is the inherent goal of the promotion
campaign. Large-scale manual annotations on practical data set
convey both the effectiveness of our proposed algorithm, and an
in-depth understanding of PCQ.
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关键词
Promotion campaign,Query auto completion,Spam Detection
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