JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE) ›› 2018, Vol. 48 ›› Issue (3): 17-24.doi: 10.6040/j.issn.1672-3961.0.2017.411

Previous Articles     Next Articles

Item embedding classification method for E-commerce

LONG Bai1, ZENG Xianyu1, LI Zhi1,2, LIU Qi1*   

  1. 1. Anhui Province Key Laboratory of Big Data Analysis and Application, School of Computer Science and Technology, University of Science and Technology of China, Hefei 230000, Anhui, China;
    2. School of Software Engineering, University of Science and Technology of China, Hefei 230000, Anhui, China
  • Received:2017-05-17 Online:2018-06-20 Published:2017-05-17

PDF (PC)

1102

Abstract: Inspired by the Word Embedding Model word2vec, which proved higly successful in the field of Natural Language Processing in recent years, two Item Embedding models item2vec and w-item2vec were proposed. By modeling users behaviour sequences, both item2vec and w-item2vec projected the items to distributed representations in vector space. The vectors of items represented the properties of items and could be used to measure the relations between items. By means of this property, we could categorize products effectively and efficiently. Experimental results showed that methods were conducted on a real-world dataset and w-item2vec achieved an accuracy of nearly 50% for item categorization by using only 10% of the items for training. Two proposed models outperformed other methods obviously.

Key words: item categorization, item emebedding, behavior modeling, word embedding, E-commerce

CLC Number: 

  • TP391
[1] 中华人民共和国商务部:中国电子商务报告(2016)[EB/OL].(2017-06-14)[2017-06-28]. http://images.mofcom.gov.cn/dzsws/ 201706/20170621110205702.pdf
[2] SHEN D, RUVINI J D, SARWAR B. Large-scale item categorization for e-commerce[C] //Proceedings of the 21st ACM International Conference on Information and Knowledge Management. Hawaii, USA: ACM, 2012: 595-604.
[3] CHEN J, WARREN D. Cost-sensitive learning for large-scale hierarchical classification[C] //Proceedings of the 22nd ACM International Conference on Information and Knowledge Management. San Francisco, USA: ACM, 2013: 1351-1360.
[4] DEKEL O, KESHET J, SINGER Y. Large margin hierarchical classification[C] //Proceedings of the 21st International Conference on Machine Learning. Banff, Canada: ACM, 2004: 27.
[5] DAS P, XIA Y, LEVINE A, et al. Large-scale taxonomy categorization for noisy product listings[C] //Proceedings of IEEE International Conference on Big Data. Honolulu, USA: IEEE, 2017:3885-3894.
[6] DIMITROVSKI I, KOCEV D, KITANOVSKI I, et al. Improved medical image modality classification using a combination of visual and textual features[J]. Computerized Medical Imaging and Graphics, 2015, 39(1): 14-26.
[7] RUSSAKOVSKY O, DENG J, SU H, et al. Imagenet large scale visual recognition challenge[J]. International Journal of Computer Vision, 2015, 115(3): 211-252.
[8] LIU Q, ZENG X, ZHU H, et al. Mining indecisiveness in customer behaviors[C] // Proceedings of IEEE International Conference on Data Mining. Barcelona, Spain: IEEE, 2016:281-290.
[9] HINTON G E, MCCLELLAND J L, RUMELHART D E. Distributed representations[M]. New York, USA: Encyclopedia of Cognitive Science. John Wiley & Sons, Ltd, 2006:77-109.
[10] MIKOLOV T, SUTSKEVER I, CHEN K, et al. Distributed representations of words and phrases and their compositionality[J]. Advances in Neural Information Processing Systems, 2013, 26(1):3111-3119.
[11] MIKOLOV T, CHEN K, CORRADO G, et al. Efficient estimation of word representations in vector space [C] // Proceedings of International Conference on Learning Representations. Scottsdale, USA: ICLR, 2013:1-12.
[12] PEROZZI B, Al-RFOU R, SKIENA S. Deepwalk: Online learning of social representations[C] //Proceedings of the 20th ACM International Conference on Knowledge Discovery and Data Mining. New York, USA: ACM, 2014: 701-710.
[13] GROVER A, LESKOVEC J. node2vec: Scalable feature learning for networks[C] //Proceedings of the 22nd ACM International Conference on Knowledge Discovery and Data Mining. San Francisco, USA: ACM, 2016: 855-864.
[14] GRBOVIC M, DJURIC N, RADOSAVLJEVIC V, et al. Context-and content-aware embeddings for query rewriting in sponsored search[C] //Proceedings of the 38th International ACM Conference on Research and Development in Information Retrieval. Santiago, Chile: ACM, 2015: 383-392.
[15] PRESS S J, WELSON S. Choosing between logistic regression and discriminant analysis[J]. Journal of the American Statistical Association, 1978, 73(364): 699-705.
[16] SUYKENS J A K, VANDEWALLE J. Least squares support vector machine classifiers[J]. Neural Processing Letters, 1999, 9(3): 293-300.
[17] JANSEN Bernard J, SPINK A, BLAKELY C, et al. Defining a session on web search engines: research articles[J]. Journal of the American Society for Information Science and Technology, 2007, 58(6): 862-871.
[18] GUTHRIE D, ALLISON B, LIU W, et al. A closer look at skip-gram modelling[C] //Proceedings of the 5th international Conference on Language Resources and Evaluation(LREC-2006). Genoa, Italy: ELRA, 2006: 1-4.
[19] GUTMANN M U, HYVÄRINEN A. Noise-contrastive estimation of unnormalized statistical models, with applications to natural image statistics[J]. Journal of Machine Learning Research, 2012, 13(2): 307-361.
[20] MNIH A, TEH Y W. A fast and simple algorithm for training neural probabilistic language models [C] // Proceedings of International Coference on International Conference on Machine Learning. Omnipress, Scotland: PMLR, 2012:419-426.
[21] MNIH A, KAVUKCUOGLU K. Learning word embeddings efficiently with noise-contrastive estimation [C] // Proceedings of Advances in Neural Information Processing Systems. Lake Tahoe, USA: NIPS, 2013: 2265-2273.
[22] SARWAR B, KARYPIS G, KONSTAN J, et al. Item-based collaborative filtering recommendation algorithms[C] //Proceedings of the 10th International Conference on World Wide Web. Hong Kong, China: ACM, 2001: 285-295.
[23] MNIH A, SALAKHUTDINOV R R. Probabilistic matrix factorization[C] // Proceedings of Advances in Neural Information Processing Systems. Whistler, Canada: NIPS, 2008: 1257-1264.
[1] DENG Bin, ZHANG Zongbao, ZHAO Wenmeng, LUO Xinhang, WU Qiuwei. Cloud-edge collaborative and graph neural network based load forecasting method for electric vehicle charging stations [J]. Journal of Shandong University(Engineering Science), 2025, 55(5): 62-69.
[2] LI Erchao, ZHANG Zhizhao. Online dynamic demand vehicle routing planning [J]. Journal of Shandong University(Engineering Science), 2024, 54(5): 62-73.
[3] YANG Jucheng, WEI Feng, LIN Liang, JIA Qingxiang, LIU Jianzheng. A research survey of driver drowsiness driving detection [J]. Journal of Shandong University(Engineering Science), 2024, 54(2): 1-12.
[4] XIAO Wei, ZHENG Gengsheng, CHEN Yujia. Named entity recognition method combined with self-training model [J]. Journal of Shandong University(Engineering Science), 2024, 54(2): 96-102.
[5] Gang HU, Lemeng WANG, Zhiyu LU, Qin WANG, Xiang XU. Importance identification method based on multi-order neighborhood hierarchical association contribution of nodes [J]. Journal of Shandong University(Engineering Science), 2024, 54(1): 1-10.
[6] Jiachun LI,Bowen LI,Jianbo CHANG. An efficient and lightweight RGB frame-level face anti-spoofing model [J]. Journal of Shandong University(Engineering Science), 2023, 53(6): 1-7.
[7] Yujiang FAN,Huanhuan HUANG,Jiaxiong DING,Kai LIAO,Binshan YU. Resilience evaluation system of the old community based on cloud model [J]. Journal of Shandong University(Engineering Science), 2023, 53(5): 1-9, 19.
[8] Ying LI,Jiankun WANG. The classification of mild cognitive impairment based on supervised graph regularization and information fusion [J]. Journal of Shandong University(Engineering Science), 2023, 53(4): 65-73.
[9] WU Yanli, LIU Shuwei, HE Dongxiao, WANG Xiaobao, JIN Di. Poisson-gamma topic model of describing multiple underlying relationships [J]. Journal of Shandong University(Engineering Science), 2023, 53(2): 51-60.
[10] YU Mingjun, DIAO Hongjun, LING Xinghong. Online multi-object tracking method based on trajectory mask [J]. Journal of Shandong University(Engineering Science), 2023, 53(2): 61-69.
[11] LIU Xing, YANG Lu, HAO Fanchang. Finger vein image retrieval based on multi-feature fusion [J]. Journal of Shandong University(Engineering Science), 2023, 53(2): 118-126.
[12] LIU Fangxu, WANG Jian, WEI Benzheng. Auxiliary diagnosis algorithm for pediatric pneumonia based on multi-spatial attention [J]. Journal of Shandong University(Engineering Science), 2023, 53(2): 135-142.
[13] YU Yixuan, YANG Geng, GENG Hua. Multimodal hierarchical keyframe extraction method for continuous combined motion [J]. Journal of Shandong University(Engineering Science), 2023, 53(2): 42-50.
[14] HUANG Huajuan, CHENG Qian, WEI Xiuxi, YU Chuchu. Adaptive crow search algorithm with Jaya algorithm and Gaussian mutation [J]. Journal of Shandong University(Engineering Science), 2023, 53(2): 11-22.
[15] ZHANG Hao, LI Ziling, LIU Tong, ZHANG Dawei, TAO Jianhua. A technology prediction model based on fuzzy Bayesian networks with sociological factors [J]. Journal of Shandong University(Engineering Science), 2023, 53(2): 23-33.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
[1] LI Kan . Empolder and implement of the embedded weld control system[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2008, 38(4): 37 -41 .
[2] LAI Xiang . The global domain of attraction for a kind of MKdV equations[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2006, 36(1): 87 -92 .
[3] YU Jia yuan1, TIAN Jin ting1, ZHU Qiang zhong2. Computational intelligence and its application in psychology[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2009, 39(1): 1 -5 .
[4] LI Liang, LUO Qiming, CHEN Enhong. Graph-based ranking model for object-level search
[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2009, 39(1): 15 -21 .
[5] CHEN Rui, LI Hongwei, TIAN Jing. The relationship between the number of magnetic poles and the bearing capacity of radial magnetic bearing[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2018, 48(2): 81 -85 .
[6] WANG Bo,WANG Ning-sheng . Automatic generation and combinatory optimization of disassembly sequence for mechanical-electric assembly[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2006, 36(2): 52 -57 .
[7] ZHANG Ying,LANG Yongmei,ZHAO Yuxiao,ZHANG Jianda,QIAO Peng,LI Shanping . Research on technique of aerobic granular sludge cultivationby seeding EGSB anaerobic granular sludge[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2006, 36(4): 56 -59 .
[8] Yue Khing Toh1， XIAO Wendong2， XIE Lihua1. Wireless sensor network for distributed target tracking: practices via real test bed development[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2009, 39(1): 50 -56 .
[9] SUN Weiwei， WANG Yuzhen. Finite gain stabilization of singlemachine infinite bus system subject to saturation[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2009, 39(1): 69 -76 .
[10] SUN Yu-li,LI De-fa,ZUO Dun-wen,QI mei . [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2006, 36(6): 19 -23 .
Copyright 2018 © Editorial office of Journal of Shandong University (Engineering Science)
Supported by Beijing Magtech Co.Ltd