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On Conceptually Simple Algorithms for Variants of Online Bipartite Matching [article]

Allan Borodin, Denis Pankratov, Amirali Salehi-Abari
2017 arXiv   pre-print
We present a series of results regarding conceptually simple algorithms for bipartite matching in various online and related models. We first consider a deterministic adversarial model.  ...  We then consider a natural greedy algorithm in the online stochastic IID model---MinDegree. This algorithm is an online version of a well-known and extensively studied offline algorithm MinGreedy.  ...  Since the k-pass Category-Advice algorithm is a Ranking-based algorithm, the same conclusion holds for k-pass Category-Advice.  ... 
arXiv:1706.09966v1 fatcat:vtkzsgn6tvcopokn6xspw2jyka

On Conceptually Simple Algorithms for Variants of Online Bipartite Matching [chapter]

Allan Borodin, Denis Pankratov, Amirali Salehi-Abari
2018 Lecture Notes in Computer Science  
We present a series of results regarding conceptually simple algorithms for bipartite matching in various online and related models. We first consider a deterministic adversarial model.  ...  We then consider a natural greedy algorithm in the online stochastic IID model -Min-Degree. This algorithm is an online version of a well-known and extensively studied offline algorithm MinGreedy.  ...  Since the k-pass Category-Advice algorithm is a Ranking-based algorithm, the same conclusion holds for k-pass Category-Advice.  ... 
doi:10.1007/978-3-319-89441-6_19 fatcat:2koqimajsvhljb5p6zvcflwt54

A new family of online algorithms for category ranking

Koby Crammer, Yoram Singer
2002 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval - SIGIR '02  
We describe a new family of topic-ranking algorithms for multi-labeled documents. The motivation for the algorithms stems from recent advances in online learning algorithms.  ...  On both corpora the algorithms we present outperform adaptations to topic-ranking of Rocchio's algorithm and the Perceptron algorithm.  ...  We also would like to acknowledge the financial support of EU project KerMIT No. IST-2000-25341 and the KerMIT group members for useful discussions.  ... 
doi:10.1145/564376.564404 dblp:conf/sigir/CrammerS02 fatcat:tbkfoiz6onhs7btunashgtnriu

A new family of online algorithms for category ranking

Koby Crammer, Yoram Singer
2002 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval - SIGIR '02  
We describe a new family of topic-ranking algorithms for multi-labeled documents. The motivation for the algorithms stems from recent advances in online learning algorithms.  ...  On both corpora the algorithms we present outperform adaptations to topic-ranking of Rocchio's algorithm and the Perceptron algorithm.  ...  We also would like to acknowledge the financial support of EU project KerMIT No. IST-2000-25341 and the KerMIT group members for useful discussions.  ... 
doi:10.1145/564400.564404 fatcat:fwz7m7ydjnhitkgmarfg2iqexm

An Experimental Study of Algorithms for Online Bipartite Matching [article]

Allan Borodin, Christodoulos Karavasilis, Denis Pankratov
2018 arXiv   pre-print
Greediness is by far the most important property of online algorithms for bipartite matching.  ...  We perform an experimental study of algorithms for online bipartite matching under the known i.i.d. input model with integral types.  ...  We thank Michael Kapralov for discussing BahmaniKapralov algorithm.  ... 
arXiv:1808.04863v1 fatcat:2cxtryl53fdvjjwcprhxswovdm

Predicting purchase behaviors from social media

Yongzheng Zhang, Marco Pennacchiotti
2013 Proceedings of the 22nd international conference on World Wide Web - WWW '13  
We specifically aim at understanding if the user's profile information in a social network (for example Facebook) can be leveraged to predict what categories of products the user will buy from (for example  ...  This paper presents a system for predicting a user's purchase behaviors on e-commerce websites from the user's social media profile.  ...  We are also grateful to the authors of LibLinear and SVM light for providing great tools for our study.  ... 
doi:10.1145/2488388.2488521 dblp:conf/www/ZhangP13 fatcat:fqjj22puzrc5heqk55ykivcr5m

Page-level Optimization of e-Commerce Item Recommendations [article]

Chieh Lo, Hongliang Yu, Xin Yin, Krutika Shetty, Changchen He, Kathy Hu, Justin Platz, Adam Ilardi, Sriganesh Madhvanath
2021 arXiv   pre-print
These are typically in the form of a series of modules or carousels, with each module containing a set of recommended items.  ...  In our online A/B test, our framework improved click-through rate by 2.48% and purchase-through rate by 7.34% over a static configuration.  ...  categories, even when they are looking at the IDP for a specific pair of shoes.  ... 
arXiv:2108.05891v1 fatcat:pthcwahr5vfsbflvanmtwy6rxy

Matchings with Group Fairness Constraints: Online and Offline Algorithms [article]

Govind S. Sankar, Anand Louis, Meghana Nasre, Prajakta Nimbhorkar
2021 arXiv   pre-print
We consider the problem of assigning items to platforms in the presence of group fairness constraints. In the input, each item belongs to certain categories, called classes in this paper.  ...  Under these restrictions, the problem continues to remain NP-hard but admits approximation algorithms with small approximation factors. We also implement some of the algorithms.  ...  We are grateful to the anonymous reviewers for their comments. AL was supported in part by SERB Award ECR/2017/003296 and a Pratiksha Trust Young Investigator Award.  ... 
arXiv:2105.09522v1 fatcat:fyzpflxyqrc7hdaqfbtfsqbiua

Unsupervised Medical Entity Recognition and Linking in Chinese Online Medical Text

Jing Xu, Liang Gan, Mian Cheng, Quanyuan Wu
2018 Journal of Healthcare Engineering  
Then, the categories of the candidate entities are determined using a distributed semantic-based approach.  ...  However, the diverse and ambiguous nature of the surface forms gives rise to a great difficulty for ME identification.  ...  In addition, we use the phrase "category signature" to denote the vector of an entity category.  ... 
doi:10.1155/2018/2548537 pmid:29849994 pmcid:PMC5932451 fatcat:rgixfe7iijc2dnp54e2jndn2xe

Page 3429 of Mathematical Reviews Vol. , Issue 89F [page]

1989 Mathematical Reviews  
A Sperner family is saturated if {A}U.7 is not a Sperner family for any A ¢ 7. Section 3 contains some results about Sperner families. The main results of the paper are in Section 4.  ...  3429 the family of minimum keys in the closure 2. By the minimality, it follows that A,B €. %(2), A#B imply A ¢ B. The families having this property are called Sperner families.  ... 

A Rule-based Approach for Identifying Obesity and Its Comorbidities in Medical Discharge Summaries

N. K. Mishra, D. M. Cummo, J. J. Arnzen, J. Bonander
2009 JAMIA Journal of the American Medical Informatics Association  
The documents were then classified using a simple scoring algorithm based on a mapping of the assertion types to possible judgment categories.  ...  Conclusions: As shown by its ranking in the challenge results, this approach performed relatively well under conditions in which limited training data existed for some judgment categories.  ...  Due to concerns that the limited amount of training data in two of the four judgment categories would substantially hinder the effectiveness of a machine learning algorithm, we opted to use a rule-based  ... 
doi:10.1197/jamia.m3086 pmid:19390102 pmcid:PMC2705262 fatcat:3or6glsahbciljz4gzficue5ru

A Hybrid Explanations Framework for Collaborative Filtering Recommender Systems

Shay Ben-Elazar, Noam Koenigstein
2014 ACM Conference on Recommender Systems  
Given a specific user and a recommended item, the algorithm utilizes the user's personal information as well as global information (e.g., item similarities, metadata) in order to rank item tags based on  ...  We present a flexible explanations framework for collaborative filtering recommender systems.  ...  Additional examples of tag modules are: 1) prior multiplier for specific tags which serve as better / worst fit for explanations; 2) TF-IDF weights based on item descriptions; 3) a binary or weighted vector  ... 
dblp:conf/recsys/Ben-ElazarK14 fatcat:pfbynx4tl5ck5nc5fd4cdz45ma

Quantitatively Partitioning Microbial Genomic Traits among Taxonomic Ranks across the Microbial Tree of Life [article]

Taylor M. Royalty, Andrew D. Steen
2019 bioRxiv   pre-print
We quantified the enrichment of clusters of orthologous gene functional categories (COG-FCs) as a proxy for traits within the lineages of 13,735 cultured and uncultured microbial lineages from a custom-curated  ...  Here, we adopted cluster of orthologous group functional categories as a scheme to describe the genomic contents of microbes, which can be applied to any microbial lineage for which genomes are available  ...  The relative importance of 74 taxonomic ranks did not change in this analysis, and all the additional explanatory power was 75 partitioned to the ranks of phylum, order, family, and genus.  ... 
doi:10.1101/520973 fatcat:scuxoag2jvbtbdv7l6don6goyu

Variational Inference for Category Recommendation in E-Commerce platforms [article]

Ramasubramanian Balasubramanian, Venugopal Mani, Abhinav Mathur, Sushant Kumar, Kannan Achan
2021 arXiv   pre-print
Category recommendation for users on an e-Commerce platform is an important task as it dictates the flow of traffic through the website.  ...  The structure of this temporal behavior can be harvested for better category recommendations and in this work, we attempt to harness this through variational inference.  ...  While the Metapath2Vec algorithm does a good job of clustering together relevant categories, there is no real distinction between the coffee accessories family and the coffee powders family.  ... 
arXiv:2104.07748v2 fatcat:cc7z6olimjgtxjxwdfwnq7nnly

Understanding Consumer Preferences from Social Media Data

Bradley Taylor
2019 NIM Marketing Intelligence Review  
Consumers produce enormous amounts of textual data of product reviews online.  ...  By using free, widespread online data it is completely passive, without affecting respondents or leading them into ranking or answering questions they would otherwise not even have thought of.  ...  The 4th column, using the complete dataset of 53,000 reviews, shows the correct ranking for Brand A and B -the major volume drivers in the category -and confusion of Brands C, D, E.  ... 
doi:10.2478/nimmir-2019-0016 fatcat:2f73f53v7fbnrezypgee2gbkwa
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