Schema Matching using Machine Learning

ثبت نشده
چکیده

Schema Matching is a method of finding attributes that are either similar to each other linguistically or represent the same information. In this project, we take a hybrid approach at solving this problem by making use of both the provided data and the schema name to perform one to one schema matching and introduce creation of a global dictionary to achieve one to many schema matching. We experiment with two methods of one to one matching and compare both based on their F-scores, precision and recall. We also compare our method with the ones previously suggested and highlight differences between them. Keywords—Schema Matching, Machine Learning, SOM, Edit Distance, One to Many Matching, One to One Matching

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Database Schema Matching Using Machine Learning with Feature Selection

Schema matching, the problem of finding mappings between the attributes of two semantically related database schemas, is an important aspect of many database applications such as schema integration, data warehousing, and electronic commerce. Unfortunately, schema matching remains largely a manual, labor-intensive process. Furthermore, the effort required is typically linear in the number of sch...

متن کامل

Designing a Knowledge-based Schema Matching System for Schema Mapping

Schema mapping that provides a unified view to the users is necessary to manage schema heterogeneity among different data sources. Schema matching is a required task for schema mapping that finds semantic correspondences between entity pairs of schemas. Semi-automatic schema matching systems were developed to overcome manual works for schema mapping. However, such approaches require a high manu...

متن کامل

Schema Matching Using Machine Learningwith

Schema matching, the problem of nding mappings between the attributes of two semantically related database schemas, is an important aspect of many database applications such as schema integration, data warehousing, and electronic commerce. Unfortunately, schema matching remains largely a manual, labor-intensive process. Furthermore, the eeort required is typically linear in the number of schema...

متن کامل

CMC: Combining Multiple Schema-Matching Strategies Based on Credibility Prediction

Schema matching, which tries to find semantic correspondences between schema elements, is a key operation in data engineering. Combining multiple matching strategies is a very promising technique for schema matching. To overcome the limitations of existing combination systems and to achieve better performances, in this paper the CMC system is proposed, which combines multiple matchers based on ...

متن کامل

Managing Uncertainty in Schema Matcher Ensembles

Schema matching is the task of matching between concepts describing the meaning of data in various heterogeneous, distributed data sources. With many heuristics to choose from, several tools have enabled the use of schema matcher ensembles, combining principles by which different schema matchers judge the similarity between concepts. In this work, we investigate means of estimating the uncertai...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2017