Extending a Logic-Based Retrieval Model With Algebraic Knowledge

计算机研究与发展 ｏ ｆ Ｃ ｏ ｍ ｕ ｔ ｅ ｒ Ｒ ｅ ｓ ｅ ａ ｒ ｃ ｈ ａ ｎ ｄ Ｄ ｅ ｖ ｅ ｌ ｏ ｍ ｅ ｎ ｔ Ｊ ｏ ｕ ｒ ｎ ａ ｌ ｐ ｐ
Ｉ Ｓ Ｓ Ｎ １ ０ ０ ０ １ ２ ３ ９ Ｃ Ｎ １ １ １ ７ ７ ７ Ｔ Ｐ － ? － ? （ ） ： ， ５ ０ Ｓ ｕ ｌ ． １ ０ ３ １ ３ ２ ０ １ ３ －１ ｐ ｐ
， Ａ ｂ ｓ ｔ ｒ ａ ｃ ｔ ｉ ｔ ｈ ｔ ｈ ｅ ｄ ｅ ｖ ｅ ｌ ｏ ｍ ｅ ｎ ｔ ｏ ｆ Ｓ ｅ ｍ ａ ｎ ｔ ｉ ｃ Ｗ ｅ ｂ ａ ｎ ｄ Ｌ ｉ ｎ ｋ ｅ ｄ Ｄ ａ ｔ ａ Ｐ ｒ ｏ ｅ ｃ ｔ ｌ ａ ｒ ｅ ａ ｍ ｏ ｕ ｎ ｔ ｓ ｏ ｆ ｓ ｅ ｍ ａ ｎ ｔ ｉ ｃ Ｗ ｐ ｊ ｇ ， ｄ ａ ｔ ａ ｆ ｒ ｏ ｍ ｄ ｉ ｆ ｆ ｅ ｒ ｅ ｎ ｔ ｋ ｉ ｎ ｄ ｓ ｏ ｆ ｄ ｏ ｍ ａ ｉ ｎ ｓ ｉ ｓ ｉ ｎ ｃ ｒ ｅ ａ ｓ ｉ ｎ ｒ ａ ｉ ｄ ｌ ．Ｍ ｅ ａ ｎ ｗ ｈ ｉ ｌ ｅ ｔ ｈ ｅ ｒ ｅ ｅ ｘ ｉ ｓ ｔ ｃ ｏ ｍ ｌ ｅ ｘ ｓ ｅ ｍ ａ ｎ ｔ ｉ ｃ ｇ ｐ ｙ ｐ ｒ ｅ ａ ｔ ａ ｍ ｏ ｎ ｔ ｈ ｅ ｓ ｅ ｄ ａ ｔ ａ ．Ｔ ｈ ｅ ｃ ｏ ｍ ｌ ｅ ｘ ｃ ｏ ｒ ｒ ｅ ｌ ａ ｔ ｉ ｏ ｎ ｉ ｎ ｆ ｏ ｒ ｍ ａ ｔ ｉ ｏ ｎ ｉ ｓ ｏ ｆ ｉ ｍ ｏ ｒ ｔ ａ ｎ ｃ ｅ ｆ ｏ ｒ ａ ｓ ｓ ｏ ｃ ｉ ａ ｔ ｉ ｏ ｎ ｓ ｇ ｇ ｐ ｐ ｒ ｅ ｓ ｅ ａ ｒ ｃ ｈ ｅ ｒ ｓ ． Ｃ ｏ ｎ ｖ ｅ ｎ ｔ ｉ ｏ ｎ ａ ｌ ｒ ｕ ｌ ｅ ｂ ａ ｓ ｅ ｄ ｒ ｅ ａ ｓ ｏ ｎ ｉ ｎ ｅ ｎ ｉ ｎ ｅ ｓ ｉ ｎ ｅ ｖ ｉ ｔ ａ ｂ ｌ ｍ ｅ ｅ ｔ ｔ ｈ ｅ ｂ ｏ ｔ ｔ ｌ ｅ ｎ ｅ ｃ ｋ ｏ ｆ ｃ ｏ ｍ ｕ ｔ ｉ ｎ － ｇ ｇ ｙ ｐ ｇ ｒ ｏ ｂ ｌ ｅ ｍ ｅ ｒ ｆ ｏ ｒ ｍ ａ ｎ ｃ ｅ ａ ｎ ｄ ｓ ｃ ａ ｌ ａ ｂ ｉ ｌ ｉ ｔ ｗ ｈ ｅ ｎ ｔ ｈ ｅ ａ ｒ ｅ ｕ ｓ ｅ ｄ ｔ ｏ ｓ ｏ ｌ ｖ ｅ ｔ ｈ ｅ ｏ ｆ ｒ ｅ ａ ｓ ｏ ｎ ｉ ｎ ｏ ｖ ｅ ｒ ｂ ｉ ｓ ｅ ｍ ａ ｎ ｔ ｉ ｃ ｐ ｐ ｙ ｙ ｇ ｇ ，ｗ ａ ｅ ｒ ｒ ｅ ｓ ｅ ｎ ｔ ａ ｃ ｒ ｏ ｓ ｓ ｌ ａ ｒ ｅ ｖ ｏ ｌ ｕ ｍ ｎ ｏ ｎ ｔ ｏ ｌ ｏ ｉ ｅ ｓ ．Ｉ ｎ ｔ ｈ ｉ ｓ ｅ ａ ｎ ｏ ｖ ｅ ｌ ｄ ｉ ｓ ｔ ｒ ｉ ｂ ｕ ｔ ｅ ｄ ｒ ｅ ａ ｓ ｏ ｎ ｉ ｎ ｄ ａ ｔ ａ ｐ ｐ ｐ ｇ ｇ ｇ ，ｗ ｆ ｒ ａ ｍ ｅ ｗ ｏ ｒ ｋ ｆ ｏ ｒ ｂ ｉ ｓ ｅ ｍ ａ ｎ ｔ ｉ ｃ ｄ ａ ｔ ａ ｂ ａ ｓ ｅ ｄ ｏ ｎ Ｈ ａ ｄ ｏ ｏ ｏ ｒ ｒ ｅ ｓ ｏ ｎ ｄ ｉ ｎ ｌ ｅ ａ ｌ ｓ ｏ ｄ ｅ ｓ ｉ ｎ ａ ｒ ｅ ａ ｓ ｏ ｎ ｉ ｎ ｇ ｐ．Ｃ ｐ ｇ ｙ ｇ ｇ ｒ ｏ ｅ ｒ ｔ ｒ ｏ ｔ ｏ ｔ ｅ ｓ ｓ ｔ ｅ ｍ ｂ ａ ｓ ｅ ｄ ｏ ｎ ｃ ｈ ａ ｉ ｎ ｔ ｏ ｄ ｉ ｓ ｃ ｏ ｖ ｅ ｒ ｔ ｈ ｅ ｉ ｍ ｌ ｉ ｃ ｉ ｔ ａ ｓ ｓ ｏ ｃ ｉ ａ ｔ ｉ ｏ ｎ ｓ ｂ ｅ ｔ ｗ ｅ ｅ ｎ ｄ ｉ ｆ ｆ ｅ ｒ ｅ ｎ ｔ ｐ ｐ ｙ ｐ ｙ ｐ ｙ ｐ ，ｗ ｅ ｎ ｔ ｉ ｔ ｉ ｅ ｓ ｆ ｒ ｏ ｍ ｔ ｈ ｅ ｌ ａ ｒ ｅ ｓ ｃ ａ ｌ ｅ ｓ ｅ ｍ ａ ｎ ｔ ｉ ｃ ｄ ａ ｔ ａ ． Ｉ ｎ ｏ ｕ ｒ ｅ ｘ ｅ ｒ ｉ ｍ ｅ ｎ ｔ ｅ ｆ ｏ ｃ ｕ ｓ ｏ ｎ ｔ ｈ ｅ ｓ ｅ ｍ ａ ｎ ｔ ｉ ｃ ａ ｓ ｓ ｏ ｃ ｉ ａ ｔ ｉ ｏ ｎ － ｇ ｐ ｒ ｏ ｔ ｏ ｔ ｅ ｄ ｉ ｓ ｃ ｏ ｖ ｅ ｒ ｉ ｎ ｔ ｈ ｅ ａ ｒ ｅ ａ ｓ ｏ ｆ ｍ ｅ ｄ ｉ ｃ ａ ｌ ａ ｎ ｄ ｌ ｉ ｆ ｅ ｓ ｃ ｉ ｅ ｎ ｃ ｅ ｓ ．Ｔ ｈ ｅ ｅ ｘ ｅ ｒ ｉ ｍ ｅ ｎ ｔ ａ ｌ ｒ ｅ ｓ ｕ ｌ ｔ ｓ ｉ ｎ ｄ ｉ ｃ ａ ｔ ｅ ｔ ｈ ｅ ｐ ｙ ｐ ｙ ｐ ， ｓ ｓ ｔ ｅ ｍ ａ ｃ ｈ ｉ ｅ ｖ ｅ ｓ ｈ ｉ ｈ ｅ ｒ ｆ ｏ ｒ ｍ ａ ｎ ｃ ｅｓ ｃ ａ ｌ ａ ｂ ｉ ｌ ｉ ｔ ａ ｎ ｄ ｒ ｅ ｃ ｉ ｓ ｉ ｏ ｎ． ｙ ｇ ｐ ｙ ｐ ； ； Ｋ ｅ ｗ ｏ ｒ ｄ ｓ ａ ｄ ｏ ｏ ｓ ｅ ｍ ａ ｎ ｔ ｉ ｃ ｒ ｅ ａ ｓ ｏ ｎ ｉ ｎ ｂ ｉ ｄ ａ ｔ ａ ｃ ｈ ａ ｉ ｎ； ｄ ｉ ｓ ｔ ｒ ｉ ｂ ｕ ｔ ｅ ｄ ｆ ｒ ａ ｍ ｅ ｗ ｏ ｒ ｋ ｒ ｏ ｅ ｒ ｔ Ｈ ｐ； ｇ ｇ ｐ ｐ ｙ ｙ ） ） 和关 联 数 据 集 项 目 （ 的 不 断 发 展， 各领域的 摘 要 随着语义万维网 （ ｓ ｅ ｍ ａ ｔ ｉ ｃ Ｗ ｅ ｂ ｌ ｉ ｎ ｋ ｅ ｄ ｄ ａ ｔ ａ ｒ ｏ ｅ ｃ ｔ ｐ ｊ 同时 ， 这些大规模语义数据之间存在着复杂 的 语 义 关 联 性 ， 这些关联信息的 语义数据正在大规模扩增 ． 挖掘对于研究者来说有着重要的意义 ． 为解决传统推理引擎在进行大规模 语 义 数 据 推 理 时 存 在 的 计 算 性能和可扩展性不足等问题 ， 提出了一种基于 Ｈ 并且设计了相应 ａ ｄ ｏ ｏ ｐ 的语义大数据分布式推理框架 ， ） 的基于属性链 （ 的原型推理系统来高效地发现海量语义数据中潜在的有价值的信息 ． 实 ｒ ｏ ｅ ｒ ｔ ｃ ｈ ａ ｉ ｎ ｐ ｐ ｙ 验主要关注于医疗和生命科学领域各本体之间的语义关联发现 ， 实验结果表明 ， 该推理系统取得了良好 — — 扩展性以及准确性 ． 的性能 — 语义推理 ； 大数据 ； 属性链 ； 分布式框架 关键词 Ｈ ａ ｄ ｏ ｏ ｐ；

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