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A Best Match KNN-based Approach for Large-scale Product Categorization

Haohao Hu, Runjie Zhu, Yuqi Wang, Wenying Feng, Xing Tan, Jimmy Xiangji Huang
2018 Annual International ACM SIGIR Conference on Research and Development in Information Retrieval  
This paper gives a system description of the KNN-based algorithm for solving the product classification problem.  ...  the real-life product categorizing problem.  ...  Definition 2: BM25: BM25 (Best Match) [5, 15, 16 ] is a probabilistic ranking function which ranks the matching documents based on their degree of relevance to the given user queries.  ... 
dblp:conf/sigir/HuZWFTH18 fatcat:3sttcxunq5g5neme6y6dxas4mq


2013 International journal on artificial intelligence tools  
This paper investigates ways to automatically discover a categorization of human faces from a collection of unlabeled face images without relying on predefined visual cues.  ...  It has been demonstrated that using face categorization as a precursor step to face recognition improves recognition rates and leads to more graceful errors. 1 Although face categorization using common  ...  George Bebis is a Visiting Professor in the College of Computer and Information Sciences at King Saud University, Riyadh 11543, Saudi Arabia.  ... 
doi:10.1142/s0218213012500297 fatcat:tvjyxnqwrnb4daleplhpyv5wju

A Comparative Study on Different Types of Approaches to Text Categorization

Pratiksha Y. Pawar, S. H. Gawande
2012 International Journal of Machine Learning and Computing  
This paper presents a comparative study on different types of approaches to text categorization.  ...  Text Categorization is a pattern classification task for text mining and necessary for efficient management of textual information systems.  ...  Therefore, machine learning based approaches are replacing rule based one for text categorization.  ... 
doi:10.7763/ijmlc.2012.v2.158 fatcat:aum7nxk3kba75h4liw53u554bu

Video event classification using string kernels

Lamberto Ballan, Marco Bertini, Alberto Del Bimbo, Giuseppe Serra
2009 Multimedia tools and applications  
The bag-of-words (BoW) approach has proven to be successful for the categorization of objects and scenes in images, but it is unable to model temporal information between consecutive frames.  ...  In this paper we present a method to introduce temporal information for video event recognition within the BoW approach.  ...  The authors thank Filippo Amendola for his support in the preparation of the experiments.  ... 
doi:10.1007/s11042-009-0351-3 fatcat:eo3yu7k7gfgmhg3b43mlja3z6y

Don't Classify, Translate: Multi-Level E-Commerce Product Categorization Via Machine Translation [article]

Maggie Yundi Li and Stanley Kok and Liling Tan
2018 arXiv   pre-print
In our experiments on two large real-world datasets, we show that our approach achieves better predictive accuracy than a state-of-the-art classification system for product categorization.  ...  Conventional methods for product categorization are typically based on machine learning classification algorithms.  ...  We thank RIT for the collaboration, support and computation resources for our experiments. We also thank Ali Cevahir for his advice on the CUDeep-related experiments.  ... 
arXiv:1812.05774v1 fatcat:ki545ztt4rcynhnzg4gyg3pwz4

Recognition of Consumer Preference by Analysis and Classification EEG Signals

Mashael Aldayel, Mourad Ykhlef, Abeer Al-Nafjan
2021 Frontiers in Human Neuroscience  
The performance of EEG-based preference detection systems depends on a suitable selection of feature extraction techniques and machine learning algorithms.  ...  The performance of the proposed deep neural network (DNN) outperforms KNN and SVM in accuracy, precision, and recall; however, RF achieved results similar to those of the DNN for the same dataset.  ...  ACKNOWLEDGMENTS The authors would like to thank the deanship of scientific research for funding and supporting this research through the initiative of DSR Graduate Students Research Support (GSR) at King  ... 
doi:10.3389/fnhum.2020.604639 pmid:33519402 pmcid:PMC7838383 fatcat:wfyyr52hozdrtemkfmoidyc7aq

KNN based Machine Learning Approach for Text and Document Mining

Vishwanath Bijalwan, Vinay Kumar, Pinki Kumari, Jordan Pascual
2014 International Journal of Database Theory and Application  
In this paper, we first categorize the documents using KNN based machine learning approach and then return the most relevant documents. . He is person with lot of potential.  ...  Text Categorization (TC), also known as Text Classification, is the task of automatically classifying a set of text documents into different categories from a predefined set.  ...  The survey is oriented towards the various probabilistic approach of KNN Machine Learning algorithm for which the text categorization aims to classify the document with optimal accuracy.  ... 
doi:10.14257/ijdta.2014.7.1.06 fatcat:pqpgqlmmdvazbf2xeobyckuzly

Machine learning approach for text and document mining [article]

Vishwanath Bijalwan, Pinki Kumari, Jordan Pascual, Vijay Bhaskar Semwal
2014 arXiv   pre-print
In this paper, we first categorize the documents using KNN based machine learning approach and then return the most relevant documents.  ...  Text Categorization (TC), also known as Text Classification, is the task of automatically classifying a set of text documents into different categories from a predefined set.  ...  The survey is oriented towards the various probabilistic approach of KNN Machine Learning algorithm for which the text categorization aims to classify the document with optimal accuracy.  ... 
arXiv:1406.1580v1 fatcat:dhjetreamfdqfddtba3bnyjwdu

Using the Mathematical Model on Precision Marketing with Online Transaction Data Computing

Jun Wu, Li Shi, Guangshu Xu, Yu-Hsi Yuan, Sang-Bing Tsai, Weiyi Hao, Jiesong Jiang
2021 Mathematical Problems in Engineering  
In this paper, a decision-making system for precision marketing is presented to deal with real-world problems based on real e-business data collected in a company in Beijing.  ...  Based on the processed data, the authors analyzed consumer purchasing behaviors using three classic recommendation algorithms and made a performance comparison of the three algorithms.  ...  Acknowledgments is work was supported, in part, by Funds for First-Class Discipline Construction (XK1802-5) and BUCT (G-JD202002).  ... 
doi:10.1155/2021/5539300 doaj:2402ae2f34654cf5b2cab04662413fda fatcat:flpfl6azkjhrxfuf3rbvtnzu4e

Sketch Recognition by Ensemble Matching of Structured Features

Yi Li, Yi-Zhe Song, Shaogang Gong
2013 Procedings of the British Machine Vision Conference 2013  
To this end, we present a method for the representation and matching of sketches by exploiting not only local features but also global structures of sketches, through a star graph based ensemble matching  ...  We further show that by encapsulating holistic structure matching and learned bag-of-features models into a single framework, notable recognition performance improvement over the state-of-the-art can be  ...  on large-scale datasets where ambiguities commonly exist [15] .  ... 
doi:10.5244/c.27.35 dblp:conf/bmvc/LiSG13 fatcat:4e5hckggobeydhsi3r7yrnxvve

Photometric redshift estimation for quasars by integration of KNN and SVM

Bo Han, Hong-Peng Ding, Yan-Xia Zhang, Yong-Heng Zhao
2016 Research in Astronomy and Astrophysics  
The massive photometric data collected from multiple large-scale sky surveys offer significant opportunities for measuring distances of celestial objects by photometric redshifts.  ...  However, catastrophic failure is still an unsolved problem for a long time and exists in the current photometric redshift estimation approaches (such as k-nearest-neighbor).  ...  crossmatch among multiple surveys avoiding cross-match efforts especially for the growing of large survey data.  ... 
doi:10.1088/1674-4527/16/5/074 fatcat:r6vwinnvwbdfvghgebguwywjdm

Phenotyping Women Based on Dietary Macronutrients, Physical Activity, and Body Weight Using Machine Learning Tools

Ramyaa Ramyaa, Omid Hosseini, Giri P. Krishnan, Sridevi Krishnan
2019 Nutrients  
For categorical prediction, SVM performed the best (54.5% accuracy), followed closely by the bagged tree ensemble and kNN algorithms.  ...  A classifier was used to phenotype subjects into the identified clusters, with MAEs <5 kg for 15% of the test set (n = ~2000).  ...  The method that worked best for these data was a local, instance-based learning method called k-nearest neighbors (kNN, explained below).  ... 
doi:10.3390/nu11071681 pmid:31336626 pmcid:PMC6682952 fatcat:btit4mlznzebldi4ao6tdphqua

Automatic Learning Framework for Pharmaceutical Record Matching

Jose Luis Lopez-Cuadrado, Israel Gonzalez-Carrasco, Jesus Leonardo Lopez-Hernandez, Paloma Martinez-Fernandez, Jose Luis Martinez-Fernandez
2020 IEEE Access  
This article presents a framework for pharmaceutical record matching based on machine learning techniques in a big data environment.  ...  Finally, the production environment is simulated by generating a huge amount of combinations of records and predicting the matches.  ...  In this case, the best combination is achieved again by the RFO classifier. Finally, Table 5 presents the results for the categorical approach.  ... 
doi:10.1109/access.2020.3024558 fatcat:axlboxy3mzdkpizphyagqkrrnq

Critical Analysis of Data Mining Techniques on Medical Data

Zahid Ullah, Muhamma Fayaz, Asif Iqbal
2016 International Journal of Modern Education and Computer Science  
We examine for discovering the locally frequent patterns through data mining technique in terms of cost performance speed and accuracy.  ...  The use of Data mining techniques on medical data is dramatically soar for determining helpful things which are used in decision making and identification.  ...  Decision tree categorizes the rules which are helpful for the physicians to take the best decision.  ... 
doi:10.5815/ijmecs.2016.02.05 fatcat:fefglbwju5bsdal3g22ipwk4f4

Integrating Machine Learning With Microsimulation to Classify Hypothetical, Novel Patients for Predicting Pregabalin Treatment Response Based on Observational and Randomized Data in Patients With Painful Diabetic Peripheral Neuropathy

Joe Alexander Jr, Roger A Edwards, Luigi Manca, Roberto Grugni, Gianluca Bonfanti, Birol Emir, Ed Whalen, Steve Watt, Marina Brodsky, Bruce Parsons
2019 Pragmatic and Observational Research  
An ensemble combination of two instance-based machine learning techniques best accommodated different data types (dichotomous, categorical, continuous) and performed better than either technique alone  ...  Coarsened exact matching of OS and RCT patients was used and a hierarchical cluster analysis was implemented.  ...  We assessed a novel patient's alignment with a cluster based on three approaches: (1) the kNN method alone, (2) the SFCM method alone, and (3) the combination of the kNN and SFCM together (hereon labeled  ... 
doi:10.2147/por.s214412 pmid:31802967 pmcid:PMC6827520 fatcat:f4cfjrz5mnhn3egzii4exyyofq
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