Applications of approximate word matching in information retrieval
CIKM '97 Proceedings of the sixth international conference on Information and knowledge management
A guided tour to approximate string matching
ACM Computing Surveys (CSUR)
Improved approximate pattern matching on hypertext
Theoretical Computer Science
Statistics-Based Summarization - Step One: Sentence Compression
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
The mathematics of statistical machine translation: parameter estimation
Computational Linguistics - Special issue on using large corpora: II
Automatic evaluation of summaries using N-gram co-occurrence statistics
NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
Improved statistical alignment models
ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics
Impedance coupling in content-targeted advertising
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Example-based machine translation using efficient sentence retrieval based on edit-distance
ACM Transactions on Asian Language Information Processing (TALIP)
Finding advertising keywords on web pages
Proceedings of the 15th international conference on World Wide Web
Training linear SVMs in linear time
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Keyword Generation for Search Engine Advertising
ICDMW '06 Proceedings of the Sixth IEEE International Conference on Data Mining - Workshops
A semantic approach to contextual advertising
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Keyword generation for search engine advertising using semantic similarity between terms
Proceedings of the ninth international conference on Electronic commerce
Advertising keyword suggestion based on concept hierarchy
WSDM '08 Proceedings of the 2008 International Conference on Web Search and Data Mining
A noisy-channel approach to contextual advertising
Proceedings of the 1st international workshop on Data mining and audience intelligence for advertising
Using the wisdom of the crowds for keyword generation
Proceedings of the 17th international conference on World Wide Web
Statistical machine translation
ACM Computing Surveys (CSUR)
Optimizing relevance and revenue in ad search: a query substitution approach
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Search advertising using web relevance feedback
Proceedings of the 17th ACM conference on Information and knowledge management
Online expansion of rare queries for sponsored search
Proceedings of the 18th international conference on World wide web
Towards intent-driven bidterm suggestion
Proceedings of the 18th international conference on World wide web
Advertising keyword generation using active learning
Proceedings of the 18th international conference on World wide web
Learning phoneme mappings for transliteration without parallel data
NAACL '09 Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Probabilistic first pass retrieval for search advertising: from theory to practice
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Proceedings of the 20th ACM international conference on Information and knowledge management
Advertising Keywords Recommendation for Short-Text Web Pages Using Wikipedia
ACM Transactions on Intelligent Systems and Technology (TIST)
Data-driven response generation in social media
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
A simple word trigger method for social tag suggestion
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Automatic generation of listing ads by reusing promotional texts
Proceedings of the 12th International Conference on Electronic Commerce: Roadmap for the Future of Electronic Business
BidTerm Suggestion for Advertising Webpages
ASONAM '12 Proceedings of the 2012 International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2012)
Multi-label learning with millions of labels: recommending advertiser bid phrases for web pages
Proceedings of the 22nd international conference on World Wide Web
Automated snippet generation for online advertising
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
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One of the most prevalent online advertising methods is textual advertising. To produce a textual ad, an advertiser must craft a short creative (the text of the ad) linking to a landing page, which describes the product or service being promoted. Furthermore, the advertiser must associate the creative to a set of manually chosen bid phrases representing those Web search queries that should trigger the ad. For efficiency, given a landing page, the bid phrases are often chosen first, and then for each bid phrase the creative is produced using a template. Nevertheless, an ad campaign (e.g., for a large retailer) might involve thousands of landing pages and tens or hundreds of thousands of bid phrases, hence the entire process is very laborious. Our study aims towards the automatic construction of online ad campaigns: given a landing page, we propose several algorithmic methods to generate bid phrases suitable for the given input. Such phrases must be both relevant (that is, reflect the content of the page) and well-formed (that is, likely to be used as queries to a Web search engine). To this end, we use a two phase approach. First, candidate bid phrases are generated by a number of methods, including a (mono-lingual) translation model capable of generating phrases contained within the text of the input as well as previously "unseen" phrases. Second, the candidates are ranked in a probabilistic framework using both the translation model, which favors relevant phrases, as well as a bid phrase language model, which favors well-formed phrases. Empirical evaluation based on a real-life corpus of advertiser-created landing pages and associated bid phrases confirms the value of our approach, which successfully re-generates many of the human-crafted bid phrases and performs significantly better than a pure text extraction method.