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Contextual Ranking of Keywords Using Click Data
2009
Proceedings / International Conference on Data Engineering
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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
2014
Proceedings of the 23rd International Conference on World Wide Web - WWW '14 Companion
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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
2018
Proceedings of the 18th ACM/IEEE on Joint Conference on Digital Libraries - JCDL '18
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2018 pre-print arXiv:1804.06426v1 fatcat:yvro5m6yzfap7l3jaxp7lenlky
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
2020
ICT Express
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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
2010
Proceeding of the 33rd international ACM SIGIR conference on Research and development in information retrieval - SIGIR '10
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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
2008
Proceeding of the 17th international conference on World Wide Web - WWW '08
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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]
2011
Advanced Topics in Information Retrieval
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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
2014
Proceedings of the 37th international ACM SIGIR conference on Research & development in information retrieval - SIGIR '14
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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]
2021
arXiv
pre-print
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2021 pre-print arXiv:2108.04976v1 fatcat:6snkxsueyfbclgq4bciveqd7ui
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
2009
2009 Sixth International Conference on Information Technology: New Generations
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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
2011
Proceedings of the 20th international conference companion on World wide web - WWW '11
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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]
2014
arXiv
pre-print
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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
2017
IJARCCE
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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
2008
Proceedings of the international conference on Web search and web data mining - WSDM '08
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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
2014
Social Science Research Network
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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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