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LEARNING USER INTERESTS FOR RECOMMENDATIONS IN BUSINESS INTELLIGENCE INTERACTIONS

机译:学习用户对商务智能交互中的建议的兴趣

摘要

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for improving recommendation to users in data intelligence systems. In one aspect, a method includes the actions of receiving a current observation describing an interaction of a user with a data intelligence system; identifying a current user interest based on the current observation, wherein past observations of the user with the data intelligence system are clustered to form user interests in a Markov model; using the Markov model and based on the current user interest, determining a next user interest from the user interests; extracting a one past observation from the determined next user interest based on a selection criterion and a threshold, wherein the selection criterion is based on how closely the at least one past observation matches the current observation; and sending a recommendation to the user based on the past observation.
机译:方法,系统和装置,包括编码在计算机存储介质上的计算机程序,用于改善对数据智能系统中用户的推荐。在一个方面,一种方法包括以下动作:接收描述用户与数据智能系统的交互的当前观察;基于当前观察,识别当前用户兴趣,其中,将用户过去使用数据智能系统的观察聚类以形成马尔可夫模型中的用户兴趣;使用马尔可夫模型,并基于当前用户兴趣,从用户兴趣中确定下一个用户兴趣;基于选择标准和阈值从确定的下一个用户兴趣中提取一个过去的观察,其中所述选择标准基于所述至少一个过去的观察与当前观察的匹配程度;并根据过去的观察向用户发送推荐。

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