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机构地区:[1]武汉大学信息资源研究中心,武汉430072 [2]华中师范大学计算机科学系,武汉430079
出 处:《情报学报》2012年第2期166-173,共8页Journal of the China Society for Scientific and Technical Information
基 金:基金项目:国家自然科学基金项目“企业竞争情报智能分析模型与方法研究”(项目批准号:71073121);教育部人文社会科学重点研究基地重大项目“基于智能信息处理的知识挖掘技术及其应用研究”(项目批准号:08JJD870225).
摘 要:动态竞争情报是企业在复杂多变的竞争环境中取得成功的关键。针对传统的竞争情报分析模型无法有效地对信息资源进行深层次的多维分析,获取语义层面的动态竞争情报,本文构建了基于联机分析挖掘的动态竞争情报多维语义分析模型。该模型利用竞争情报领域本体指导目标信息的采集与监控和实体与关系的抽取,实现竞争情报的语义组织和存储;设计了一种基于语义的多维关联分析算法进行语义层面的数据挖掘、学习和推理,实现竞争情报多维语义挖掘和知识发现。实验结果表明,该模型取得了很好的预期效果,显著提高了情报分析的深度与广度和情报分析的准确率与效率。Dynamic competitive intelligence is a key factor for an enterprise to succeed in the complicated and varied competitive environment. A dynamic competitive intelligence multi-dimensional semantic analysis model based on on-line analytical mining is constructed to make up for the deficiency of traditional competitive intelligence analysis model that it can not analyze information resources at deep level in multi-dimensions effectively to acquire dynamic competitive intelligence at semantic level. This model adopts competitive intelligence domain ontology to guide the collecting and monitoring to target information and the exacting to entities and relations, realizing the semantic organization and storage of competitive intelligence. Furthermore, a semantic-based multi-dimensional association analysis algorithm is designed to complete data mining, learning and reasoning at semantic level, implementing semantic mining and knowledge discovery of competitive intelligence. Experiment results demonstrate that this model achieved a good anticipative effect. It improves the depth, width, accuracy and efficiency of intelligence analysis dramatically.
分 类 号:TP311.13[自动化与计算机技术—计算机软件与理论]
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