Intuit, Inc.

Onn Bar

Alexander Zhicharevich

Shlomi Medalion

Elik Sror

Sigalit Bechler

Shir Meir Lador

Erez Katzenelson

Shimon Shahar

Ariel Simhon

Gal Keinan

In one aspect, the present disclosure relates to a method of generating business descriptions performed by a server, said method may include: receiving a plurality of invoices, each invoice being associated with a business of a plurality of businesses; extracting a plurality of texts from the plurality of invoices; embedding the plurality of texts to a vector space to obtain a plurality of invoice vectors; generating a plurality of clusters in the vector space, each cluster of the plurality of clusters comprising at least one invoice vector of the plurality of invoice vectors; generating a description for a cluster, the description for the cluster representing all invoice vectors assigned to the cluster; for each business of the plurality of businesses that has at least one invoice vector assigned to the cluster, associating the business with the description; and indexing the plurality of businesses within a database by the generated descriptions.

Systems and methods of business categorization and service recommendation

Methods and systems classify and cluster invoice data. An invoice is obtained. A category vector is generated from an invoice string of the invoice with a dense layer of a machine learning model that includes an embedding layer, a neural network layer, and the dense layer. A suggestion is selected with a selection engine and in response to comparing the category vector to a set of clusters. The suggestion is presented.

Invoice data classification and clustering

A method for recommending offerings to a business may include: receiving a request for recommended business offerings from a device; receiving business data associated with a business from the device, the business data comprising invoice data associated with the business; embedding the business data to a vector space to obtain a business vector, the vector space comprising a plurality of other vectors associated with other businesses; calculating a relation metric between the business vector and a vector of the plurality of other vectors, the vector being associated with a second business, the relation metric representing a degree of relation between the business and the second business; determining that the relation metric is above a pre-defined threshold value; and responsive to the determining, sending business data associated with the second business to the device, the business data associated with the second business comprising invoice data associated with the second business.

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Tel Aviv, Israel

Onn Bar