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A collaborative filtering approach to ad recommendation using the query-ad click graph

Tasos Anastasakos, Dustin Hillard, Sanjay Kshetramade, Hema Raghavan
2009 Proceeding of the 18th ACM conference on Information and knowledge management - CIKM '09  
The method builds on a collaborative filtering approach to discover new ads related to a query using a click graph.  ...  We propose a new technique to determine the relevance of an ad document for a search query using click-through data.  ...  We apply an approach from collaborative filtering to first determine query-query similarity on this bipartite graph.  ... 
doi:10.1145/1645953.1646267 dblp:conf/cikm/AnastasakosHKR09 fatcat:3dmfwdft6jhjrgmgkiwc7lob24

Query Suggestion and Recommendation Using Bipartite Graph and K-Means Clustering
IJARCCE - Computer and Communication Engineering

Dr. E.S. SAMUNDEESWARI, BRINDHA S
2014 IJARCCE  
out query suggestion and recommends query and URL"s using Bipartite graph and Kmeans clustering.  ...  The first challenge is that it is not easy to recommend latent semantically relevant results to users. The second challenge is to take into account the personalization feature.  ...  On the other hand, Collaborative-filtering systems use patterns in user ratings to make recommendations. Both types of recommender systems require significant data resources.  ... 
doi:10.17148/ijarcce.2014.31137 fatcat:znxk3mwojjhnxb2qlibfa2imjq

Exploiting web scraping in a collaborative filtering- based approach to web advertising

Eloisa Vargiu, Mirko Urru
2012 Artificial intelligence research  
To this end, we propose a collaborative filtering-based Web advertising system aimed at finding the most relevant ads for a generic Web page by exploiting Web scraping.  ...  Web scraping is the set of techniques used to automatically get some information from a website instead of manually copying it.  ...  In their work, collaborative filtering is exploited to discover new ads related to a query using a click graph.  ... 
doi:10.5430/air.v2n1p44 fatcat:3qa7yuraszfbngclp7l65ttdmq

Metaphor

Azarias Reda, Yubin Park, Mitul Tiwari, Christian Posse, Sam Shah
2012 Proceedings of the 21st ACM international conference on Information and knowledge management - CIKM '12  
Related search recommendation is one of several mechanisms used for improving members' search experience in finding relevant results to their queries.  ...  Third, we introduce a query length model for capturing bias in recommendation click behavior. We also discuss some of the practical concerns in deploying related search recommendations.  ...  Collaborative Filtering The first signal we use to generate related search recommendations is based on collaborative filtering techniques.  ... 
doi:10.1145/2396761.2396847 dblp:conf/cikm/RedaPTPS12 fatcat:4nttbjperngi5dj46fjtivsswe

Query Click and Text Similarity Graph for Query Suggestions [chapter]

D. Sejal, K. G. Shailesh, V. Tejaswi, Dinesh Anvekar, K. R. Venugopal, S. S. Iyengar, L. M. Patnaik
2015 Lecture Notes in Computer Science  
In this paper, we have proposed a general method for query suggestion by combining two graphs: (1) query click graph which captures the relationship between queries frequently clicked on common URLs and  ...  It can be used for recommendation tasks like query, image, and product suggestion.  ...  First, a method for deriving item similarity is developed from a sample of collaborative filter data. Then, the sample similarity is used to train an optimal distance metric over audio descriptors.  ... 
doi:10.1007/978-3-319-21024-7_22 fatcat:lbx7vcdnwjhvhdj2vcyxovibbi

A Line in the Sand: Recommendation or Ad-hoc Retrieval? [article]

Surya Kallumadi, Bhaskar Mitra, Tereza Iofciu
2018 arXiv   pre-print
as a collaborative filtering approach.  ...  The popular approaches to recommendation and ad-hoc retrieval tasks are largely distinct in the literature.  ...  As this approach only considers past track-playlist membership information, we expect this method to recommend tracks similar to the collaborative filtering approach.  ... 
arXiv:1807.08061v1 fatcat:d5gwop5yuvgybecwd2hxszqrae

A Practical Solution to the ACM RecSys Challenge 2018

Tan Nghia Duong, Viet Duc Than, Trong Hiep Tran, Thi Hong Anh Pham, Van Hoang Anh Nguyen, Hoang Nam Tran
2018 2018 5th NAFOSTED Conference on Information and Computer Science (NICS)  
as a collaborative filtering approach.  ...  The popular approaches to recommendation and ad-hoc retrieval tasks are largely distinct in the literature.  ...  As this approach only considers past track-playlist membership information, we expect this method to recommend tracks similar to the collaborative filtering approach.  ... 
doi:10.1109/nics.2018.8606818 fatcat:a7bciwo7vzdz7nh3wfn33ojd2e

Web Graph based query suggestion for Text and Image
IJARCCE - Computer and Communication Engineering

S. Dhivya, T.A. Sangeetha
2015 IJARCCE  
The view recommendation user URL access details to provide the user URL access details, it is used to the user can easily identify which one is the best URL for the given query.  ...  The Graph query suggestion construct the Bipartite directed graph, based on the given queries and the access URLs. In addition Find Query Suggestion is constructed for domain wise.  ...  Collaborative Filtering According to Collaborative filtering is valuable in ecommerce and for direct recommendations for music, movies, news etc [5] .  ... 
doi:10.17148/ijarcce.2015.4174 fatcat:wc6k4bcowzfb7noxobsmkow6re

OntoInfoG++: A Knowledge Fusion Semantic Approach for Infographics Recommendation

Gerard Deepak, Adithya Vibakar, A. Santhanavijayan
2021 International Journal of Interactive Multimedia and Artificial Intelligence  
The approach models user topic of interest from the Query Words, Current User-Clicks, and from standard Knowledge Stores like the BibSonomy, DBpedia, Wikidata, LOD Cloud, and crowd sourced Ontologies.  ...  As humans tend to improvise and learn on a constant basis, the need for visualizing and recommending knowledge is increasing.  ...  The authors thank God the Eternal Father and Lord Jesus Christ for providing the required knowledge and insights for carrying our this work.  ... 
doi:10.9781/ijimai.2021.12.005 fatcat:pjyiovkvwzfcljkvhdwzcqe4k4

An Efficient Concept-based Mining Model for Deriving User Profiles

P. Sasikala, V. Vidhya
2012 International Journal of Applied Information Systems  
Collaborative filtering filters information about a user based on a collection of user profiles that are already built from the extracted preferences.  ...  Based on these accurate and up-to-date user profiles, relationships between users can be mined to perform Collaborative Filtering (CF) thereby allowing users with the same interests to share their profiles  ...  The advantages with this approach include: It is easy to create and use, new data can be added easily and incrementally.  ... 
doi:10.5120/ijais12-450187 fatcat:xifhtifycnb2rjxnij3ixe367u

Context-aware Deep Model for Entity Recommendation in Search Engine at Alibaba [article]

Qianghuai Jia, Ningyu Zhang, Nengwei Hua
2019 arXiv   pre-print
We evaluate our approach using large-scale, real-world search logs from a widely used commercial Chinese search engine.  ...  Results from online A/B test suggest that the impression efficiency of click-through rate increased by 5.1% and page view increased by 5.5%.  ...  We are grateful to our cooperative team -search engineering team. We also thank the anonymous reviewers for their valuable comments and suggestions that help improve the quality of this manuscript.  ... 
arXiv:1909.04493v1 fatcat:eg7pou6l55ajpddguwp4n4lngi

User Response Prediction in Online Advertising [article]

Zhabiz Gharibshah, Xingquan Zhu
2021 arXiv   pre-print
Recent years have witnessed a significant increase in the number of studies using computational approaches, including machine learning methods, for user response prediction.  ...  The prosperity of online campaigns is a challenge in online marketing and is usually evaluated by user response through different metrics, such as clicks on advertisement (ad) creatives, subscriptions  ...  Following similar approaches, clustering or collaborative filter based approaches are also proposed to recommend ads to users.  ... 
arXiv:2101.02342v2 fatcat:clgefamcd5fmbeg5ephizy3zqu

Query Recommendation for Long Tail Queries-A Review Paper

Anand PrasadGupta, Sunita Yadav
2012 International Journal of Computer Applications  
Some query recommendation method do not covers the unseen and rare queries but some of them covers these queries by some additional feature added such as generalize the query token of input query by a  ...  Query recommendation methods are powerful technique to generate related queries or alternate queries as a query suggestion for original query which is given by user in the search engine first time.  ...  used a "content-ignorant" approach and a graph-based iterative clustering method was used to cluster both the URLs and queries [4] .  ... 
doi:10.5120/4880-7315 fatcat:novefvdflbaotiw6xfyo6key5m

Learning to Predict Ad Clicks Based on Boosted Collaborative Filtering

Teng-Kai Fan, Chia-Hui Chang
2010 2010 IEEE Second International Conference on Social Computing  
The experiments are conducted based on datasets collected from a social finance web site called Morgenstern. We performed a series of comparison experiments between filtering approaches.  ...  In this study, we first propose the notion of social filtering and compare it with content-based filtering and collaborative filtering for advertisement allocation in a social network.  ...  ACKNOWLEDGMENT The authors would like to thank the anonymous reviewers for helpful comments on this study.  ... 
doi:10.1109/socialcom.2010.37 dblp:conf/socialcom/FanC10 fatcat:5fqbfbil2bf5tns3walugxonly

Ad Recommendation for Sponsored Search Engine via Composite Long-Short Term Memory

Dejiang Kong, Fei Wu, Siliang Tang, Yueting Zhuang
2016 Proceedings of the 2016 ACM on Multimedia Conference - MM '16  
In this paper we address ad recommendation problem that finding and ranking the most relevant ads with respect to users' search queries.  ...  Due to the click sparsity, the conventional methods can hardly model the both interand intra-relations among users, queries and ads.  ...  For example, [1] uses their fine-designed query-ad click graph to better discover similarities between queries and leverage the Collaborative Filtering(CF) approach Permission to make digital or hard  ... 
doi:10.1145/2964284.2967254 dblp:conf/mm/KongWTZ16 fatcat:5arbneyfondrljj5bh3jaaugaa
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