Importance

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Abstract

In one aspect, a computer-implemented method of real-estate entity segmentation includes classifying a set of property attributes of one or more real-estate entities using a logistic regression method. The real-estate entities are taken from a realtor's client contact list. A probability of a real-estate transaction occurring for each of the one or more real-estate entities is determined based on the set of property attributes of the one or more real-estate entities. A step includes identifying that a real-estate entity is more likely being sold or listed when the probability of a real-estate transaction occurring is above a specified threshold. The real-estate entity that is more likely being sold or listed is included in a clustering data set. A step includes implementing a fuzzy-C means clustering algorithm on all or a portion of the clustering data set to obtain a cluster center for a specified set of the property attributes. The real-estate entity is classified to a real-estate segment based on a location of the real entity in the cluster. The real-estate entity is added to the real-estate segment.

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First Claim