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Contextual Ranking of Keywords Using Click Data

Utku Irmak, Vadim von Brzeski, Reiner Kraft
2009 Proceedings / International Conference on Data Engineering  
We utilize click through data obtained from a large scale user-centric entity detection system -Contextual Shortcuts -to train a model to rank the extracted concepts, and evaluate the resulting model extensively  ...  again based on their click through data.  ...  who helped developing and building the Contextual Shortcuts platform.  ... 
doi:10.1109/icde.2009.76 dblp:conf/icde/IrmakBK09 fatcat:6gtfi6er5rhnxctcvpduiwoxx4

Automatic keywords generation for contextual advertising

Pengqi Liu, Javad Azimi, Ruofei Zhang
2014 Proceedings of the 23rd International Conference on World Wide Web - WWW '14 Companion  
A monetization parameter, predicted from historical search keyword performance, is also used to rank potential keywords in order to balance the RPM (Revenue Per 1000 Matches) and relevance.  ...  Contextual Advertising (CA) is an important area in the industry of online advertising.  ...  EXPERIMENTS Data Sets We used 6 months search queries in Bing with corresponding clicked URLs. First, for each URL, we extract the candidate keywords.  ... 
doi:10.1145/2567948.2577361 dblp:conf/www/LiuAZ14 fatcat:n4gwrajhr5ftzdageaizc5nsvm

Contextualised Browsing in a Digital Library's Living Lab

Zeljko Carevic, Sascha Schüller, Philipp Mayr, Norbert Fuhr
2018 Proceedings of the 18th ACM/IEEE on Joint Conference on Digital Libraries - JCDL '18  
The mean rank of the first clicked document (measured as mean first relevant - MFR) was 4.52 using a non-contextualised ranking compared to 3.04 when re-ranking the result lists based on similarity to  ...  Furthermore, we observed that both contextual approaches show a noticeably higher click-through rate.  ...  As most users click only on one suggested document, we use the rank position of the first clicked document as quality criterion.  ... 
doi:10.1145/3197026.3197054 dblp:conf/jcdl/CarevicSMF18 fatcat:colboqy2n5h7fes6gmxvhc2dui

Identifying machine learning techniques for classification of target advertising

Jin-A Choi, Kiho Lim
2020 ICT Express  
The paper also identifies an underexamined area, algorithm-based detection of click frauds, to illustrate how machine learning approaches can be integrated to preserve the viability of online advertising  ...  This study investigates and classifies various machine learning techniques that are used to enhance targeted online advertising.  ...  Two-stages of learning to rank approach based CTR prediction algorithm for contextual advertising were also proposed [8] .  ... 
doi:10.1016/j.icte.2020.04.012 fatcat:5qnbssw625chhfeeqkwzkgcjxm

Ranking for the conversion funnel

Abraham Bagherjeiran, Andrew O. Hatch, Adwait Ratnaparkhi
2010 Proceeding of the 33rd international ACM SIGIR conference on Research and development in information retrieval - SIGIR '10  
In contextual advertising advertisers show ads to users so that they will click on them and eventually purchase a product.  ...  We propose a ranking method that globally balances the goals of all advertisers, while simultaneously improving overall performance.  ...  FEATURE CONSTRUCTION Our training data consists of click logs from a major contextual ad network.  ... 
doi:10.1145/1835449.1835476 dblp:conf/sigir/BagherjeiranHR10 fatcat:ayeji7nwcbc3jmos7r4x4awr2u

Keyword extraction for contextual advertisement

Xiaoyuan Wu, Alvaro Bolivar
2008 Proceeding of the 17th international conference on World Wide Web - WWW '08  
Contextually relevant links to eBay assets on third party sites is one example of such advertisement avenues. Keyword extraction is the task at the core of any contextual advertisement system.  ...  The proposed solution uses linear and logistic regression models learnt from human labeled data, combined with document, text and eBay specific features.  ...  Table 1 lists a set of features related to Web page, which are potentially useful to rank keywords.  ... 
doi:10.1145/1367497.1367723 dblp:conf/www/WuB08 fatcat:abmegfeylbdo7kiugvnx2hr2da

Digital Advertising: An Information Scientist's Perspective [chapter]

James G. Shanahan, Goutham Kurra
2011 Advanced Topics in Information Retrieval  
Digital online advertising is a form of promotion that uses the Internet and World Wide Web for the express purpose of delivering marketing messages to attract customers.  ...  data-centric processes that enable highly targeted, personalized, performance based advertising.  ...  Most of the major search engines (Bing, Google, Yahoo, Yandex) rank ads and price clicks using ECPM or yield-based ranking.  ... 
doi:10.1007/978-3-642-20946-8_9 fatcat:rycs7flw75fzflspvrza4lvuo4

Towards context-aware search with right click

Aixin Sun, Chii-Hian Lou
2014 Proceedings of the 37th international ACM SIGIR conference on Research & development in information retrieval - SIGIR '14  
How to extract the right contextual information from the source document is the main focus of this study.  ...  The former determines from which text component (e.g., title, meta-data, or paragraphs containing the selected query) to extract contextual information; the latter determines which words or phrases to  ...  Instead, we only consider the contextual information from the source document of a right-click query.  ... 
doi:10.1145/2600428.2609456 dblp:conf/sigir/SunL14 fatcat:dar4l37ugvelpn3m7gvgl5edjy

Deep Pairwise Learning To Rank For Search Autocomplete [article]

Kai Yuan, Da Kuang
2021 arXiv   pre-print
In this paper, we propose a novel context-aware neural network based pairwise ranker (DeepPLTR) to improve AC ranking, DeepPLTR leverages contextual and behavioral features to rank queries by minimizing  ...  Autocomplete has been a core feature of commercial search engine.  ...  US data in 2020.  ... 
arXiv:2108.04976v2 fatcat:7uwlr6czg5b37i5dwqrq2fwdua

Improving Web Search Using Contextual Retrieval

Dilip K. Limbu, Andrew M. Connor, Russel Pears, Stephen G. MacDonell
2009 2009 Sixth International Conference on Information Technology: New Generations  
The developed system has been designed with a view to capturing both implicit and explicit user data which is used to develop a personal contextual profile.  ...  This paper reports on the development and evaluation of a system designed to tackle some of the challenges associated with contextual information retrieval from the World Wide Web (WWW).  ...  rankings, inputs, and instructions) and implicit (i.e., browsing and typing) data.  ... 
doi:10.1109/itng.2009.133 dblp:conf/itng/LimbuCPM09 fatcat:gaumdzclp5b7topwknbmzxphga

Computational advertising

Kushal S. Dave
2011 Proceedings of the 20th international conference companion on World wide web - WWW '11  
The research work focuses on the identification of various factors that contribute in retrieving and ranking the most relevant set of ads that match best with the context.  ...  Sponsored search refers to the placement of ads on search results page. Contextual advertising deals with matching advertisements to the third party web pages.  ...  We pose the problem of extraction of keywords as of classification of candidates into keyword/non-keyword. we use naïve Bayes classifier which uses following three category of features. (1)Linguistic Features  ... 
doi:10.1145/1963192.1963342 dblp:conf/www/Dave11 fatcat:vc6rwvzoorgo5csswgsqy6oupe

Improving web search using contextual retrieval [article]

Dilip K. Limbu, Andy M. Connor, Russel Pears, Stephen G. MacDonell
2014 arXiv   pre-print
The developed system has been designed with a view to capturing both implicit and explicit user data which is used to develop a personal contextual profile.  ...  This paper reports on the development and evaluation of a system designed to tackle some of the challenges associated with contextual information retrieval from the World Wide Web (WWW).  ...  rankings, inputs, and instructions) and implicit (i.e., browsing and typing) data.  ... 
arXiv:1407.6101v1 fatcat:sdd7aut2zbg23hxwwh6dwxexhe

Semantic Search on Applicant Tracking System

Le Quan Ha, Mainur Rahman
2017 IJARCCE  
Our semantic search technique has 88% -91.22% accuracy with very much quicker queries that can help users to make a search of 4 keywords of skills completed from 1 second to 28 seconds.  ...  The relevant structured data items are then returned to the user along with web search results.  ...  using query click log data to adjust the ranking to offer for users better web search results so that users can search more accurately and more efficiently.  ... 
doi:10.17148/ijarcce.2017.65122 fatcat:qbnnfo3hazdyhdkanjczwvupti

An empirical analysis of sponsored search performance in search engine advertising

Anindya Ghose, Sha Yang
2008 Proceedings of the international conference on Web search and web data mining - WSDM '08  
To the best of our knowledge, this is the first study that uses real world data from an advertiser and jointly estimates the effect of sponsored search advertising at a keyword level on consumer search  ...  rates, conversion rates, bid prices and keyword ranks.  ...  The data consists of the number of impressions, number of clicks, the average cost per click (CPC) which represents the bid price in the case of successful bid, the rank of the keyword, the number of conversions  ... 
doi:10.1145/1341531.1341563 dblp:conf/wsdm/GhoseY08 fatcat:azeeflx7njfdvkr5pgfowm65yy

Examining the Impact of Contextual Ambiguity on Search Advertising Keyword Performance: A Topic Model Approach

Vibhanshu Abhishek, Jing Gong, Beibei Li
2014 Social Science Research Network  
We quantify the effect of contextual ambiguity on keyword click-through performance using a hierarchical Bayesian model that allows for topic-specific effect and nonlinear position effect.  ...  We find that consumer click behaviors vary significant across keywords, and keyword category and the contextual ambiguity of the keywords significantly affect such variation.  ...  Subsequently, we quantify the effect of contextual ambiguity on keyword click-through performance using a hierarchical Bayesian model.  ... 
doi:10.2139/ssrn.2404081 fatcat:ycbzd56zwbafhf5jtrjghyvq2a
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