732 research outputs found
Heterogeneous Entity Matching with Complex Attribute Associations using BERT and Neural Networks
Across various domains, data from different sources such as Baidu Baike and
Wikipedia often manifest in distinct forms. Current entity matching
methodologies predominantly focus on homogeneous data, characterized by
attributes that share the same structure and concise attribute values. However,
this orientation poses challenges in handling data with diverse formats.
Moreover, prevailing approaches aggregate the similarity of attribute values
between corresponding attributes to ascertain entity similarity. Yet, they
often overlook the intricate interrelationships between attributes, where one
attribute may have multiple associations. The simplistic approach of pairwise
attribute comparison fails to harness the wealth of information encapsulated
within entities.To address these challenges, we introduce a novel entity
matching model, dubbed Entity Matching Model for Capturing Complex Attribute
Relationships(EMM-CCAR),built upon pre-trained models. Specifically, this model
transforms the matching task into a sequence matching problem to mitigate the
impact of varying data formats. Moreover, by introducing attention mechanisms,
it identifies complex relationships between attributes, emphasizing the degree
of matching among multiple attributes rather than one-to-one correspondences.
Through the integration of the EMM-CCAR model, we adeptly surmount the
challenges posed by data heterogeneity and intricate attribute
interdependencies. In comparison with the prevalent DER-SSM and Ditto
approaches, our model achieves improvements of approximately 4% and 1% in F1
scores, respectively. This furnishes a robust solution for addressing the
intricacies of attribute complexity in entity matching
Quantitative Measurement of Two-phase Flow by Electrical Capacitance Tomography Based on 3D Coupling Field Simulation
ONLINE SERVICE CO-CUSTOMIZATION: HOW THE PARTNER AND THE INFORMATION PRESENTATION AFFECTS TOURISTS’ CHOICE OF ONLINE TOUR SERVICES
People always travel with their friends. Some of them would like to design their travel plan together while some others would like to design their plan singly. Prior studies most focus on the single decision context. This paper investigates the collaborative customization in the joint decision and joint consumption context, and the information presentation format (attribute-based vs. bundle-based) effect on the tourists’ decision and behaviour is discussed. We also consider the relationship effect. And finally the potential theoretical contribution and practical implication are discussed
Stochastic Efficiency Analysis with a Reliability Consideration
Stochastic Data Envelopment Analysis (DEA) models have been introduced in the literature to assess the performance of operating entities with random input and output data. A stochastic DEA model with a reliability constraint is proposed in this study that maximizes the lower bound of an entity\u27s efficiency score with some pre-selected probability. We define the concept of stochastic efficiency and develop a solution procedure. The economic interpretations of the stochastic efficiency index are presented when the inputs and outputs of each entity follow a multivariate joint normal distribution
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