公开(公告)号：US20130246332A1

公开(公告)日：2013-09-19

申请号：US13873149

申请日：2013-04-29

Applicant: SALESFORCE.COM, INC

Inventor： Jari Koister

IPC: G06N5/02

CPC classification number: G06N5/02 ,  G06F16/9535 ,  G06Q30/02

Abstract: A compositional recommender framework using modular recommendation functions is described. Each modular recommendation function can use a discrete technology, such as using clustering, a database lookup, or other means. A first recommendation function can recommend to a user items, such as books to check out, automobiles to purchase, people to date, etc. Another modular recommendation function can be daisy chained with the first to recommend items that are similar or related to the first recommended items, such as users who have also checked out the same recommended book, trailers that can be towed by the recommended automobiles, or vacations booked by people that were recommended as people to date. The modular recommendation functions can be used to build customized recommendation engines for different industries.

Abstract translation: 描述了使用模块化推荐功能的组合推荐框架。 每个模块化推荐功能可以使用离散技术，例如使用聚类，数据库查找或其他方式。 第一推荐功能可以推荐给用户的物品，例如书籍检查，汽车购买，到目前为止的人等。另外模块化推荐功能可以用菊花链式连接，首先推荐与第一个相似或相关的项目 推荐的物品，如已经签出相同推荐书的用户，推荐的汽车可以拖车的预告片，或者是迄今为止推荐人员预订的假期。 模块化推荐功能可用于为不同行业构建定制推荐引擎。

公开(公告)号：US20130085745A1

公开(公告)日：2013-04-04

申请号：US13632848

申请日：2012-10-01

Applicant: Salesforce.com, Inc.

Inventor： Jari Koister ,  Antonisamy Arokiasamy ,  Kasthuri Periyakoil ,  Marcus Ericsson

IPC: G06F17/27

CPC classification number: G06F17/2785

Abstract: A method of identifying topics in a corpus that includes a plurality of text-based items begins by extracting keytext from each of the plurality of text-based items, resulting in sets of keytext. The method continues by processing the keytext sets to generate a respective semantic footprint for each of the text-based items, resulting in a plurality of semantic footprints. The semantic footprints are used to calculate similarity values for the text-based items, wherein the similarity values indicate commonality between pairs of the text-based items. The method continues by clustering the text-based items into a number of topic groups, wherein the clustering is influenced by the similarity values, and by generating a topic heading for each of the number of topic groups, resulting in a number of topic headings. Next, the text-based items are grouped into accessible topic groups associated with the topic headings.

Abstract translation: 一种识别包含多个基于文本的项目的语料库中的主题的方法通过从多个基于文本的项目中的每一个提取密钥文本，从而产生一组密钥文本。 该方法通过处理密钥文本集来继续，以针对每个基于文本的项目生成相应的语义覆盖，导致多个语义覆盖。 语义足迹用于计算基于文本的项目的相似度值，其中相似度值表示基于文本的项目对之间的共性。 该方法继续通过将基于文本的项目聚类成多个主题组，其中聚类受相似性值的影响，并且通过为每个主题组的每一个生成主题标题，导致多个主题标题。 接下来，基于文本的项目被分组成与主题标题相关联的可访问主题组。