公开(公告)号：US20100268711A1

公开(公告)日：2010-10-21

申请号：US12829766

申请日：2010-07-02

申请人： Ciya LIAO ,  Omar Alonso ,  Joaquin A. Delgado ,  Thomas H. Chang ,  Meeten Bhavsar

发明人： Ciya LIAO ,  Omar Alonso ,  Joaquin A. Delgado ,  Thomas H. Chang ,  Meeten Bhavsar

IPC分类号： G06F7/00 ,  G06F17/30

CPC分类号： G06F17/30719

摘要： Systems, methods, and other embodiments associated with automatically summarizing a document are described. One method embodiment includes computing term scores for members of a set of terms in a document to be summarized and computing sentence scores for sentences in a set of sentences in the document. The method embodiment also includes computing a set of entries for a term-sentence matrix that relates terms to sentences. The method embodiment also includes computing a dominant topic for the document and simultaneously ranking the set of terms and the set of sentences based on the dominant topic. The method embodiment provides a summarization item(s) selected from the set of terms and/or the set of sentences.

摘要翻译： 描述与自动总结文档相关联的系统，方法和其他实施例。 一个方法实施例包括计算要汇总的文档中的一组术语的成员的术语分数，以及计算文档中一组句子中的句子的句子分数。 方法实施例还包括计算用于将术语与句子相关联的术语矩阵的条目集合。 该方法实施例还包括计算文档的主导主题，并且基于主题来同时对该组语句和一组句子进行排序。 该方法实施例提供从该组项和/或一组句子中选择的摘要项目。

公开(公告)号：US20090006356A1

公开(公告)日：2009-01-01

申请号：US11769245

申请日：2007-06-27

申请人： Ciya LIAO ,  Thomas CHANG ,  Muralidhar KRISHNAPRASAD ,  Meeten BHAVSAR

发明人： Ciya LIAO ,  Thomas CHANG ,  Muralidhar KRISHNAPRASAD ,  Meeten BHAVSAR

IPC分类号： G06F7/06

CPC分类号： G06F17/30867 ,  G06F17/30699

摘要： Search term ranking algorithms can be generated and updated based on customer settings, such as where a ranking algorithm is modeled as a combination function of different ranking factors. An end user of a search system provides personalized preferences for weighted attributes, generally or for a single instance of the query. The user also can indicate the relative importance of one or more ranking factors by specifying different weights to the factors. Ranking factors can specify document attributes, such as document title, document body, document page rank, etc. Based on the attribute weights and the received user query, a ranking algorithm function will produce the relevant value for each document corresponding to the user preferences and personalization configurations.

摘要翻译： 搜索项排序算法可以根据客户设置生成和更新，例如排序算法被建模为不同排名因素的组合函数。 搜索系统的最终用户为加权属性提供个性化偏好，一般或单个查询实例。 用户还可以通过为因素指定不同的权重来指示一个或多个排名因子的相对重要性。 排名因素可以指定文档属性，如文档标题，文档正文，文档页面排名等。基于属性权重和接收到的用户查询，排序算法函数将为每个文档生成与用户偏好相对应的相关值， 个性化配置

公开(公告)号：US20090006360A1

公开(公告)日：2009-01-01

申请号：US11770027

申请日：2007-06-28

申请人： Ciya LIAO ,  Thomas Chang

发明人： Ciya LIAO ,  Thomas Chang

IPC分类号： G06F17/30

CPC分类号： G06F17/30595

摘要： An enterprise-wide query relaxative support vector machine ranking algorithm approach provides enhanced functionality for query execution in a heterogeneous enterprise environment. Improved query results are obtained by adjusting ranking functions using machine learning methods to automatically train ranking functions. The improved query results are obtained using a list of document-query pairs that are modeled as a binary classification training problem, combination function which requires ranking and learning functions to be implemented representing document attributes and metadata utilizing query relaxation techniques and adjusted ranking functions. Machine learning methods implement user feedback to automatically train ranking functions.

摘要翻译： 企业级查询放松支持向量机排名算法方法为异构企业环境中的查询执行提供了增强的功能。 通过使用机器学习方法调整排名函数来自动训练排名函数，获得改进的查询结果。 改进的查询结果是使用被建模为二进制分类训练问题的文档查询对的列表获得的，组合函数需要使用查询放松技术和调整的排序函数表示文档属性和元数据的排序和学习功能。 机器学习方法实现用户反馈，自动训练排名功能。