{"title":"An Application of Business Intelligence Based on Patent in Data Integration and Analysis","authors":"Dongsheng Zhai, Wenhui He","doi":"10.1109/WISM.2010.60","DOIUrl":null,"url":null,"abstract":"This paper suggests the structure of patent data integration and analysis based on business intelligence (BI) to help enterprises make the effective decisions about patent strategy and orientation of technological development by extracting effective information from mass data. Firstly, the patent data is acquired from heterogeneous data sources into the local database. Then, we can load the business data into the data warehouse after fulfilling the data extraction, transformation, and cleaning through extraction-transformation-loading (ETL) tools. Thirdly, the patent analysis based on key performance indicators (KPI) is performed with data mining models. Finally, the patent graphs drawn by KPI analysis can be published on the Microsoft Office Share point Server (MOSS) platform to realize information sharing and centralized management.","PeriodicalId":119569,"journal":{"name":"2010 International Conference on Web Information Systems and Mining","volume":"35 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 International Conference on Web Information Systems and Mining","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WISM.2010.60","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
This paper suggests the structure of patent data integration and analysis based on business intelligence (BI) to help enterprises make the effective decisions about patent strategy and orientation of technological development by extracting effective information from mass data. Firstly, the patent data is acquired from heterogeneous data sources into the local database. Then, we can load the business data into the data warehouse after fulfilling the data extraction, transformation, and cleaning through extraction-transformation-loading (ETL) tools. Thirdly, the patent analysis based on key performance indicators (KPI) is performed with data mining models. Finally, the patent graphs drawn by KPI analysis can be published on the Microsoft Office Share point Server (MOSS) platform to realize information sharing and centralized management.