Patent Document ID: 9208501
Application ID: 14094359

Base Claim:
1. An electronic computing device for providing a personalized information recommendation, comprising: an input/output interface, being configured to receive a first behavior data of a first user and a second behavior data of a second user, wherein the first behavior data and the second behavior data are arranged in a first period; a storage electrically connected to the input/output interface, being configured to store the first behavior data and the second behavior data; and a processor electrically connected to the storage, being configured to execute the following operations: retrieving the first behavior data and the second behavior data from the storage; establishing a first tree structure data and a second tree structure data according to the first behavior data and the second behavior data respectively by using an ontology construction algorithm; calculating a first similarity between the first tree structure data and the second tree structure data by using a similarity evaluation algorithm; analyzing the first similarity to subsume the first tree structure data and the second tree structure data into a first group by using a clustering algorithm; determining a piece of first difference information between the first tree structure data and the second tree structure data according to the first group; and generating a piece of first recommending information corresponding to the first user which is arranged in the first period according to the piece of first difference information so that a first monitor displays the piece of first recommending information.

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Claim 5:
5. The electronic computing device as claimed in claim 1 , wherein the input/output interface is further configured to receive a fourth behavior data of a fourth user, a fifth behavior data of the first user and a sixth behavior data of the second user, the fourth behavior data, the fifth behavior data and the sixth behavior data are arranged in a second period, the storage is further configured to store the fourth behavior data, the fifth behavior data and the sixth behavior data, and the processor is further configured to execute the following operations: retrieving the fourth behavior data, the fifth behavior data and the sixth behavior data from the storage; establishing a fourth tree structure data, a fifth tree structure data and a sixth tree structure data according to the fourth behavior data, the fifth behavior data and the sixth behavior data respectively by using the ontology construction algorithm; calculating a fourth similarity between the fourth tree structure data and the fifth tree structure data, a fifth similarity between the fifth tree structure data and the sixth tree structure data and a sixth similarity between the sixth tree structure data and the fourth tree structure data respectively by using the similarity evaluation algorithm; analyzing the fourth similarity, the fifth similarity and the sixth similarity to subsume the fourth tree structure data and the fifth tree structure data into a second group and subsume the fourth tree structure data, the fifth tree structure data and the sixth tree structure data into a third group by using the clustering algorithm, wherein an internal data correlation of the second group is higher than an internal data correlation of the third group; determining a piece of second difference information between the fifth tree structure data and the fourth tree structure data according to the second group; and generating a piece of second recommending information corresponding to the first user which is arranged in a second period according to the piece of second difference information so that the first monitor displays the piece of second recommending information.