Abstract: A system and method for computerized method for generating a probability score indicative of a probability that an owner will sell a real estate property, comprising: collecting from data sources a set of data associated with a plurality of owners and a plurality of commercial real estate properties (CREs) related thereto, based on a data item indicating a type of a desirable CRE; analyzing the collected set of data using a machine learning technique executed by a computer; determining, based on the analysis, a desirable CRE, and an owner associated with the desirable CRE; determining a probability that the owner will sell the desirable CRE with a certainty level above a predetermined threshold within a predefined time period; and generating, based on the analysis, a probability score that is indicative of the probability that the owner is likely to sell the desirable CRE within the predefined time period.
December 30, 2019
July 2, 2020
Skyline AI Ltd.
Or HILTCH, Guy ZIPORI, Shay BUSHINSKY, Shmuel UR
Abstract: A system and method for generating value prediction of commercial real-estate properties (CREs), comprising: receiving a location pointer associated with at least one CRE, where a location pointer is an identifying parameter associated with the CRE; extracting metadata associated with the at least one CRE; analyzing the metadata of the CRE and of comparable properties (comparables), where the analysis includes matching real estate factors of the CRE and the comparables; and generating at least one value prediction of the CRE based on the analysis.
Abstract: A method and system analyzing transactional data are provided. The method includes gathering transaction data related to a first physical entity; extracting a first set of features representing the first entity; gathering transaction data related to a second physical entity, wherein the at least one second physical entity is indirectly related to the first physical entity; extracting at least a second set of features associated with the at least one second physical entity; matching the first set of features to the second set features; and clustering the first set of features and the second set of features, when the first set of features matches the second set of features.