By Mohamed A. Sharaf, Muhammad Aamir Cheema, Jianzhong Qi
This ebook constitutes the refereed court cases of the twenty sixth Australasian Database convention, ADC 2015, held in Melbourne, VIC, Australia, in June 2015. The 24 complete papers provided including five demo papers have been conscientiously reviewed and chosen from forty three submissions. The Australasian Database convention is an annual foreign discussion board for sharing the newest learn developments and novel functions of database platforms, info pushed purposes and knowledge analytics among researchers and practitioners from around the world, really Australia and New Zealand. The project of ADC is to proportion novel learn options to difficulties of today’s details society that satisfy the desires of heterogeneous functions and environments and to spot new concerns and instructions for destiny study. ADC seeks papers from academia and offering learn on all functional and theoretical features of complicated database thought and purposes, in addition to case reviews and implementation experiences.
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Additional info for Databases Theory and Applications: 26th Australasian Database Conference, ADC 2015, Melbourne, VIC, Australia, June 4-7, 2015. Proceedings
Fang et al. Table 2. Statistics of Five Representative Classes # Attributes Class Book Film Country University Hotel DBpedia Extrac. (DBpedia) 21 53 191 21 18 48 53 360 484 216 Freebase Extrac. (Freebase) Combine (Freebase &DBpedia) 5 54 22 9 7 19 54 150 57 56 60 92 489 518 255 Intuitively, a sub-type should inherit all the properties of its super-type, so for every type/class in Freebase/DBpedia, we iteratively attach to the type/class all its super-types’/super-classes’ properties, as well as the names, labels, and descriptions/comments for these properties.
Traditional extractors simply remove the tags and extract data from the plain texts. Thus, they fail to exploit the knowledge contained in the DOM trees. In this paper, we introduce a two-step approach to extract attributes from DOM trees for ontology augmentation. We ﬁrst extract additional attributes from the DOM trees seeded by the attributes extracted from query stream and existing KBs (denoted by SEED SET(T)). We then deﬁne a set of ﬁlters to reﬁne and diﬀerentiate the attributes. 2, respectively.
Interactive information extraction with constrained conditional random ﬁelds. In: Proceedings of the 19th National Conf. on Artiﬁcal Intelligence (AAAI 2004), San Jose, California (2004) 11. : Attribute extraction and scoring: a probabilistic approach. In: Proceedings of 29th International Conference on Data Engineering (ICDE 2013), Brisbane, Australia (2013) 12. : Mining data records in web pages. In: Proceedings of the 9th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2003), New York, NY, USA (2003) 13.
Databases Theory and Applications: 26th Australasian Database Conference, ADC 2015, Melbourne, VIC, Australia, June 4-7, 2015. Proceedings by Mohamed A. Sharaf, Muhammad Aamir Cheema, Jianzhong Qi