An analytical review of XML association rules mining

Artificial Intelligence Review - Tập 43 - Trang 277-300 - 2013
Mohammad Moradi1, Mohammad Reza Keyvanpour2
1Department of Electrical, Computer and Biomedical Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran
2Department of Computer Engineering, Alzahra University, Vanak, Tehran, Iran

Tóm tắt

Over the past decade, there has been increasing interest in using extensible markup language (XML) which has made it a de facto standard for representing and exchanging data over different systems and platforms (specifically the internet). Due to the popularity of XML and with increasing numbers of XML documents, the process of knowledge discovery from this type of data has found more attention. Although in the last decade several different methods have been proposed for mining XML documents, this research field still is in its infancy compared to traditional data mining. As in relational techniques, in the case of XML documents, association rule mining has a strong research interest. In this paper we have performed a comprehensive study on all of the major works so far done on mining association rules from XML documents. The main contribution of the paper is to provide a reference point for future researches by collecting different techniques and methods concerning the topic; classifying them into a number of categories and creating a complete bibliography of the major published works. We think that this paper can help researchers in XML association rules mining domains to quickly find the current work as the basis for the future activities.

Tài liệu tham khảo

Abazeed A, Mamat A, Nasir M, Ibrahim H (2009a) Mining association rules from structured XML data. In: Proceedings of international conference on electrical engineering and informatics (ICEEI ’09), vol 02, pp 376–379 Abazeed A, Mamat A, Sulaiman MN, Ibrahim H (2009b) Scalable approach for mining association rules from structured XML data. In: Proceedings of the 2nd conference on data mining and optimization (DMO ’09), pp 5–9 Agrawal R, Izmielinski T, Swami A (1993a) Database mining: a performance perspective. IEEE Trans Knowl Data Eng 5:6:914–925 Agrawal R, Izmielinski T, Swami A (1993b) Mining association rules between sets of items in large database. In: Proceedings of the ACM SIGMOD, Washington, DC, pp 207–216 Agrawal R, Srikant R (1994) Fast algorithms for mining association rules. In: Proceeding of the 20th international conference on very large databases, pp 407–419 AliMohammadzadeh R, Rahgozar M, Zarnani A (2006a) A new model for discovering XML association rules from XML documents. Int J Appl Sci Eng Technol (IJASET), Trans Eng Comput Technol 14:365–369 AliMohammadzadeh R, Soltan S, Rahgozar M (2006b) Template guided association rule mining from XML documents. In: Proceedings of the 15th international conference on World Wide Web (WWW ’06). ACM, New York, NY, USA, pp 963–964 Braga D, Campi A, Ceri S, Klemettinen M, Lanzi PL, (2002a) Mining association rules from XML data. In: Proceedings of DEXA, (2002) (DaWaK), LNCS 2454. Aixen- Provence, France, pp 21–30 Braga D, Campi A, Ceri S, Klemettinen M, Lanzi PL (2002b) A tool for extracting XML association rules. In: Proceedings of the 14th IEEE international conference on tools with artificial intelligence (ICTAI ’02). IEEE Computer Society, Washington, DC, USA, pp 57–64 Braga D, Campi A, Ceri S, Klemettinen M, Lanzi PL (2003) Discovering interesting information in XML data with association rules. In: Proceedings of the (2003) ACM symposium on applied computing (SAC ’03). ACM, New York, NY, USA, pp 450–454 Bray T, Paoli J, Sperberg-McQueen CM (1998) Extensible markup language (XML) 1.0. World Wide Web Consortium (W3C). http://www.w3.org/TR/REC-xml Buddhakulsomsiri J, Siradeghyan Y, Zakarian A, Li X (2006) Association rule-generation algorithm for mining automotive warranty data. Int J Prod Res 44:14:2749–2770 Caneva E, Oliboni B, Quintarelli E (2009) Mining flexible association rules from XML. In: Proceedings of the (2009) EDBT/ICDT workshops (EDBT/ICDT ’09). ACM, New York, NY, USA, pp 85–92 Chen Y-L, Tang K, Shen R-J, Hu Y-H (2005) Market basket analysis in a multiple store environment. Decis Support Syst 40:2:339–354 Ding Q, Sundarraj G (2006) Association rule mining from XML data. In: Proceedings of international conference on data mining, Las Vegas, Nevada, pp 144–150 Ding Q, Ricords K, Lumpkin J (2003) Deriving general association rules from XML data. In: Proceedings of international conference on software engineering, artificial intelligence, networking, and parallel/distributed computing, Lübeck, Germany, pp 348–352 Exarchos TP, Papaloukas C, Fotiadis DI, Michalis LK (2006) An association rule mining-based methodology for automated detection of ischemic ECG beats. IEEE Trans Biomed Eng 53:8:1531–1540 Feng L, Dillon TS (2004) Mining XML-enabled association rule with templates. In: Proceedings of KDID Feng L, Dillon TS, Weigand H, Chang E (2003) An XML-enabled association rule framework. In: Proceedings of DEXA, 2003, pp 88–97 Garofalakis M, Gionis A, Rastogi R, Seshadri S, Shim K (2003) XTRACT: learning document type descriptors from XML document collections. Data Min Knowl Discov 7(1):23–56 Han J, Pei J, Yin Y (2000) Mining frequent patterns without candidate generation. In: Proceedings of ACM SIGMOD international conference on management of data, pp 1–12 Khaing MM, Thein N (2006) An efficient association rule mining For XML data. In: Proceedings of international joint conference SICE-ICASE, pp 5782–5786 Li X-Y, Yuan J-S, Kong Y-H (2007) Mining association rules from XML data with index table. In: Proceedings of international conference on machine learning and cybernetics, vol 07, pp 3905–3910 Liu H-C, Zeleznikow J, Jamil HM (2006) Logic-based association rule mining in XML documents. In: Shen H T, Li J, Li M, Ni J, Wang W (ed) Proceedings of the international conference on advanced web and network technologies, and applications (APWeb’06). Springer, Berlin, Heidelberg, pp 97–106 Mazuran M, Quintarelli E, Tanca L (2009) Mining tree-based association rules from XML documents. In: Proceedings of SEBD, pp 109–116 Meo R, Psaila G, Ceri S (1998) An extension to SQL for mining association rules. Data Min Knowl Discov 2(2):195–224 Moh C-H, Lim E-P, Ng W-K (2000) DTD-miner: a tool for mining DTD from XML documents. In: Proceedings of the second international workshop on advance issues of E-commerce and web-based information systems (WECWIS ’00). IEEE Computer Society, Washington, DC, USA, pp 144–151 Mustapha N, Sulaiman MN, Othman M, Selamat MH (2003) Fast discovery of long patterns for association rules. Int J Comput Math 80(8):967–976 Nayak R (2009) Discovering knowledge from XML documents. In: Wang J (ed) Encyclopedia of data warehousing and mining, 2nd edn, IGI Global, pp 663–668. doi:10.4018/978-1-60566-010-3.ch103 Paik J, Nam J, Lee S, Kim UM (2007) A framework for data structure-guided extraction of XML association rules. In: Shi Y, Albada G D, Dongarra J, Sloot PM, (ed) Proceedings of the 7th international conference on computational science ((ICCS ’07). Springer, Berlin, Heidelberg, Part III, pp 709–716 Paik J, Nam J, Kim WY, Ryu JS, Kim UM (2009) Mining association rules in tree structured XML data. In: Proceedings of the 2nd international conference on interaction sciences: information technology, culture and human (ICIS ’09). ACM, New York, NY, USA, pp 807–811 Paik J, Youn HY, Kim U (2005) A new method for mining association rules from a collection of XML documents. In: Gervasi O, Gavrilova ML, Kumar V, Laganà A, Lee HP (ed) Proceedings of the international conference on computational science and its applications (ICCSA’05), vol. part II. Springer, Berlin, Heidelberg, pp 936–945 Porkodi R, Bhuvaneswari V, Rajesh R, Amudha T (2009) An improved association rule mining technique for Xml data using Xquery and apriori algorithm. In: Proceedings of IEEE international advance computing conference (IACC 2009), pp 1510–1514 Rusu LI, Rahayu W, Taniar D (2006a) Extracting variable knowledge from multiversioned XML documents. In: Proceedings of the sixth IEEE international conference on data mining—workshops (ICDMW ’06). IEEE Computer Society, Washington, DC, USA, pp 70–74 Rusu LI, Rahayu W, Taniar D (2006b) Mining changes from versions of dynamic XML documents. In: Proceedings of the 1st international workshop of knowledge discovery from XML documents (KDXD 2006), vol 3915. Singapore, LNCS, pp 3–12 Shahriar MdS, Liu J (2011) On mining association rules with semantic constraints in XML. In: Proceedings of sixth IEEE international conference on digital information management (ICDIM 2011), Melbourne, Australia, Sept 26–28 Shin J, Paik J, Kim U (2006) Mining association rules from a collection of XML documents using cross filtering algorithm. In: Proceedings of the international conference on hybrid information technology (ICHIT ’06), vol 1. IEEE Computer Society, Washington, DC, USA, pp 120–126 The World Wide Web Consortium (W3C) (2004) Extensible markup language (XML) 1.0, 3rd edn, W3C Recommendation. http://www.w3.org/TR/2004/RECxml-20040204/. Accessed 14 Feb 2012 Thompson HS, Beech D, Maloney M, Mendelsohn N (2000) XML schema part 1: structures, W3C working draft. http://www.w3.org/TR/xmlschema-1/ Tsoi AC, Zhang C, Hagenbuchner M (2005) Pattern discovery on Australian medical claims data—a systematic approach. IEEE Trans Knowl Data Eng 17:10:1420–1435 Wan JWW, Dobbie G (2004) Mining association rules from XML data using XQuery. In: Proceedings of the second workshop on Australasian information security, data mining and web intelligence, and software internationalisation (ACSW Frontiers ’04), vol 32. Australian Computer Society, Inc., Darlinghurst, Australia, Australia, pp 169–174 Wang X, Cao C (2008) Mining association rules from complex and irregular XML documents using XSLT and Xquery. In: Proceedings of the international conference on advanced language processing and web information technology (ALPIT ’08). IEEE Computer Society, Washington, DC, USA, pp 314–319 World Wide Web Consortium. XQuery 1.0:An XML query language (W3C Working Draft). http://www.w3.org/TR/2002/WDxquery-20020816, Aug 2002. Accessed 3 Feb 2012 Xiao Y, Yao FG, Li Z, Dunham MH (2003) Efficient data mining for maximal frequent subtrees. In: Proceedings of the third IEEE international conference on data mining (ICDM ‘03). IEEE computer Society, Washington, DC, USA, p 379 Zao-xin L (2008) Association rules mining method from XML based on ontology. J Comput Appl 28(9): 2318–2320 Zhang M, He C (2010) Survey on association rules mining algorithms. Lect Notes Electr Eng 56:111–118 Zhang S, Zhang J, Liu H, Wang W (2005) XAR-miner: efficient association rules mining for XML data. In: Proceedings of special interest tracks and posters of the 14th international conference on World Wide Web (WWW ’05). ACM, New York, NY, USA, pp 894–895 Zhang J, Ling TW, Bruckner R, Tjoa AM, Liu H (2004) On efficient and effective association rule mining from XML data. In: 15th international conference on database and expert systems applications (DEXA’04), 30 Aug–3 Sept, Zaragoza, Spain Zhang J, Liu H, Ling TW, Bruckner RM, Tjoa AM (2006) A framework for efficient association rule mining in XML data. J Database Manag (JDM) 17(3):19–40 Zhao Q, Chen L, Bhowmick SS, Madria S (2006) XML structural delta mining: issues and challenges. Data Knowl Eng 59(3):627–651