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Information graph model and application to online advertising

Marina Danilevsky, Eunyee Koh
2013 Proceedings of the 1st workshop on User engagement optimization - UEO '13  
We present an algorithm which adapts a graph-based ranking model to the context of the problem of improving the process of serving advertisements to users.  ...  We also discuss how, in addition to serving as the basis for a classifier, this model may also provide an informative view of the data, which is not possible with black-box approaches, and which therefore  ...  In this paper, we present our Information Graph Model (IGM), a work-in-progress which adapts a graph-based ranking method to the problem of improving the process of serving advertisements to users.  ... 
doi:10.1145/2512875.2512878 dblp:conf/cikm/DanilevskyK13 fatcat:rb7r65fi2vdehi4b5fyr3dl3we

User Response Prediction in Online Advertising [article]

Zhabiz Gharibshah, Xingquan Zhu
2021 arXiv   pre-print
In this survey, we provide a comprehensive review of user response prediction in online advertising and related recommender applications.  ...  Our essential goal is to provide a thorough understanding of online advertising platforms, stakeholders, data availability, and typical ways of user response prediction.  ...  semantics information and corresponding information from a generated knowledge graph data.  ... 
arXiv:2101.02342v2 fatcat:clgefamcd5fmbeg5ephizy3zqu

Query-Variant Advertisement Text Generation with Association Knowledge [article]

Siyu Duan, Wei Li, Cai Jing, Yancheng He, Yunfang Wu, Xu Sun
2021 arXiv   pre-print
Online advertising is an important revenue source for many IT companies.  ...  Both automatic and human evaluations show that our model can generate more attractive advertisement text than baselines.  ...  ETHICAL ISSUES Industrial Application: For the industrial application, the generated ad candidates will be further checked by human annotators before added to the online advertising system to prevent fake  ... 
arXiv:2004.06438v3 fatcat:qvrd6lan5ze5rdg64bibrdbbhm

Semantic Advertising [article]

Ben Zamanzadeh, Naveen Ashish, Cartic Ramakrishnan, John Zimmerman
2013 arXiv   pre-print
Semantic Advertising is online advertising powered by semantic technology which essentially enables us to represent and reason with concepts and the meaning of things.  ...  We present the concept of Semantic Advertising which we see as the future of online advertising.  ...  semantic querying of information over the Facebook graph of concepts and relationships.  ... 
arXiv:1309.5018v1 fatcat:ddnvazemvfc2ll2ttveary3gqe

Stochastic Blockmodeling for Online Advertising

Li Chen, Matthew Patton
2015 PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE  
Online advertising is an important and huge industry.  ...  We propose two clustering algorithms to discover the intrinsic structures of websites, and compare the performance with a goodness-of-fit method and a deterministic graph partitioning method.  ...  The optimal number of clusters and covariance structure correspond to the model selection criterion by the Bayesian information criterion (BIC). Our approach is presented in Algorithm 1.  ... 
doi:10.1609/aaai.v29i1.9714 fatcat:sqos2ms7dvgpneusotcmiugyoy

Online Stochastic Weighted Matching: Improved Approximation Algorithms [chapter]

Bernhard Haeupler, Vahab S. Mirrokni, Morteza Zadimoghaddam
2011 Lecture Notes in Computer Science  
for any bipartite graph to 0.7036.  ...  In this problem, given an edge-weighted bipartite graph, nodes of one side arrive online i.i.d. according to a known probability distribution.  ...  In this problem, given a bipartite graph G(A, I, E) with advertisers A and impressions I, and a set E of edges between them. Advertisers in A are fixed and known.  ... 
doi:10.1007/978-3-642-25510-6_15 fatcat:7znngqjwffez7erha44ve35zsy

Online Social Networks: Status and Trends [chapter]

George Pallis, Demetrios Zeinalipour-Yazti, Marios D. Dikaiakos
2011 Studies in Computational Intelligence  
The rapid proliferation of Online Social Network (OSN) sites has made a profound impact on the WWW, which tends to reshape its structure, design, and utility.  ...  Additionally, it provides a state-of-the-art survey of popular OSN systems, examining their architectural designs and business models.  ...  RDF based descriptions of social data provide a rich typed graph and offer a much more powerful and significant way to represent online social networks than social graphs.  ... 
doi:10.1007/978-3-642-17551-0_8 fatcat:v4wxdsc3ubfproynb2bijpn4mq

Stochastic Blockmodeling for Online Advertising [article]

Li Chen, Matthew Patton
2014 arXiv   pre-print
Online advertising is an important and huge industry.  ...  We propose two clustering algorithms to discover the instrinsic structures of websites, and compare the performance with a goodness-of-fit method and a deterministic graph partitioning method.  ...  We are optimistic that random graph framework is valuable for online advertising research.  ... 
arXiv:1410.6714v2 fatcat:5nebqrgxbjci7o7hailsqm4mve

Issue Information

2021 System Dynamics Review  
Graphs System Dynamics Review operates an online submission and peer review system that allows authors to submit articles online and track their progress via a web interface.  ...  See online Guidelines for Authors for additional suggestions, examples, and tools to facilitate the creation of figures and graphs.  ... 
doi:10.1002/sdr.1684 fatcat:lvj6gcbpnrambcnl2cpceu4gcm

Must social networking conflict with privacy?

Jonathan Anderson, Frank Stajano
2013 IEEE Security and Privacy  
Online social networks (OSNs) have serious privacy drawbacks, some of which stem from the business model. Must this be? Is the current OSN business model the only viable one?  ...  Or can we construct alternatives that are technically and economically feasible?  ...  Building a reliable P2P network often requires exposing some amount of social graph information to the network. 15 But it's the social graph that we most want to protect!  ... 
doi:10.1109/msp.2013.23 fatcat:fdpmxw6q3vbzlodou6r3b6sdhi

Implementation of Artificial Intelligence Based Analyzer Using Multi-Agent System Approach

Norah S. Farooqi, Mohamed O. Khozium
2022 Intelligent Automation and Soft Computing  
The functionality and results are promising. This paper opens the road for the researchers to proceed toward universal BI model and the opportunity to implement new BI services.  ...  Using Business Intelligence (BI) applications is a critical factor for modern enterprises' success.  ...  The four agents represent the types of online applications required to implement the model.  ... 
doi:10.32604/iasc.2022.019060 fatcat:d36ceqnhazggfgavigwdnkpumm

Intent-Based User Segmentation with Query Enhancement

Wei Xiong, Michael Recce, Brook Wu
2013 International Journal of Information Retrieval Research  
To some extent, behavioral targeting is another application of machine learning methods to online advertising.  ...  As a rich source of information on web searchers' behavior, query logs have been utilized by advertising companies to deliver personalized advertisements and leveraged by researchers to tackle other application  ... 
doi:10.4018/ijirr.2013100101 fatcat:2sh4kotdsrh33k4etfu2o3xuoq

Context Aware Location Identification in Social Media Environment

2015 International Journal of Science and Research (IJSR)  
applications such as annotation, automatic training data acquisition, contextual advertising, and visualization.  ...  We review the research advances for enabling such applications and present a brief outlook on open issues and major opportunities.  ...  ., videos, photos, tags, users, and so on) are contextually correlated and able to boost the applications mentioned above by constructing the context graphs.  ... 
doi:10.21275/v4i11.nov151065 fatcat:74uzbph3jvb7za4u6fqx4ckrqi

Guest editorial: Interpretable AI-enabled online behavior analytics

Wei Xu, Jianshan Sun, Mengxiang Li
2022 Internet Research  
The fourth article by Runyu Chen adopts a cooperative learning model with multimodal information to predict advertising clicks.  ...  It first creates a patent knowledge graph and then leverages paths in the patent knowledge graph to achieve recommendation interpretability.  ... 
doi:10.1108/intr-04-2022-683 fatcat:gw5pdbi2mvfnnc6yada6j4jdsa

The Game Trace Archive

Yong Guo, Alexandru Iosup
2012 2012 11th Annual Workshop on Network and Systems Support for Games (NetGames)  
Finally, we discuss possible applications of the GTA in gaming area such as game resource management, Quality of Experience for players, and advertisement.  ...  We collect in the GTA traces corresponding to more than 8 million real players and more than 200 million information items, spanning over 14 operational years.  ...  We focus in this work on potential application of the GTA data to select the location and moment to integrate advertisement. 1) Integrating advertisements into games with less influence to gaming experience  ... 
doi:10.1109/netgames.2012.6404027 dblp:conf/netgames/GuoI12 fatcat:4zgpgv6zlrfgvfcrdetpxxvpzy
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