Systems and methods for determining relevance of place data

Patent metadata

Field	Value
Publication number	US-2019171755-A1
Application number	US-201715829487-A
Country	US
Kind code	A1
Filing date	Dec 1, 2017
Priority date	Dec 1, 2017
Publication date	Jun 6, 2019
Grant date	—

Abstract

Various embodiments determine relevance of place data by determining whether a place record is relevant based on a set of features associated with the place record. For a given place record, a set of features may be generated based on values of one or more attributes included in the given place record. A given place record may be processed by at least one machine learning model, such as a classifier, which receives as input a set of features of the given place record and outputs a prediction score indicating the certainty or probability that the given place record is associated with, or belongs to, a particular class. The certainty/probability of association between a given place record and a particular class can assist some embodiments in determining (e.g., predicting) whether the given place record is relevant or non-relevant for an intended use, such as a software application for a ride service.

First claim

What is claimed is:

1 . A method comprising:
accessing, by one or more hardware processors, a particular place record from a data source, the particular place record describing a particular place on a geographic map; generating, by the one or more hardware processors, a set of features for the particular place record based on a value from an attribute included in the particular place record; processing, by the one or more hardware processors, the set of features using a classifier to generate a probability that the particular place record is associated with a class label; and determining, by the one or more hardware processors, whether the particular place record is relevant based on at least the probability that the particular place record is associated with a class label.

2 . The method of claim 1 , further comprising, in response to determining that the particular place record is relevant, generating, by the one or more hardware processors, relevant place data that includes the particular place record and an associated relevance score, the associated relevance score being based on the probability.

3 . The method of claim 1 , wherein the class label represents that the particular place record is relevant to a ride-sharing service.

4 . The method of claim 1 , wherein the class label represents that the particular place record is relevant and describes an incorrect location for the particular place.

5 . The method of claim 1 , wherein the class label represents that the particular place record is relevant and describes that the particular place is closed.

6 . The method of claim 1 , wherein the class label represents that the particular place record is relevant and describes that the particular place is a private practice.

7 . The method of claim 1 , wherein the class label represents that the particular place record is not relevant to a ride-sharing service.

8 . The method of claim 1 , wherein the class label represents that the particular place record is not relevant and describes that the particular place is a private location.

9 . The method of claim 1 , wherein the class label represents that the particular place record is not relevant and describes a temporary event.

10 . The method of claim 1 , wherein the class label represents that the particular place record describes that the particular place does not exist.

11 . The method of claim 1 , wherein the generating the set of features for the particular place record comprises extracting a value from an attribute of the particular place record.

12 . The method of claim 1 , further comprising producing a set of matched place records by matching a first set of place records, from a first data source of place records, with at least a second set of place records from a second data source of place records, wherein the accessing the particular place record from the data source comprises accessing the particular place record from the set of matched place records.

13 . The method of claim 1 , further comprising in response to determining that the particular place record is relevant, processing, by the one or more hardware processors, the particular place record for accuracy, wherein the accuracy at least includes accuracy of geographic coordinates described by the particular place record.

14 . The method of claim 1 , further comprising producing a set of relevant place records for each different data source in a plurality of data sources by performing the accessing of the particular place record, the generating of the set of features, the processing of the set of features, and the determining of whether the particular place record is relevant for each place record provided the different data source, wherein the method further comprises:
producing a set of matched relevant place records by matching together place records within the sets of relevant place records for the different data sources.

15 . The method of claim 14 , further comprising processing, by the one or more hardware processors, the set of relevant place records for accuracy, wherein the accuracy at least includes accuracy of geographic coordinates described by the particular place record.

16 . The method of claim 1 , wherein the classifier comprises a binary classifier.

17 . The method of claim 1 , wherein the classifier is trained on ground truth data comprising a set of place records and a set of corresponding class labels curated by a human individual.

18 . The method of claim 1 , wherein the data source comprises a place record that is generated or maintained by a plurality of human users.

19 . A non-transitory computer storage medium comprising instructions that, when executed by a hardware processor of a device, cause the device to perform operations comprising:
accessing a particular place record from a data source, the particular place record describing a particular place on a geographic map; generating a set of features for the particular place record based on a value from an attribute included in the particular place record; processing the set of features using a classifier to generate a probability that the particular place record is associated with a class label; and determining whether the particular place record is relevant based on at least the probability that the particular place record is associated with a class label.

20 . A computer comprising:
a memory storing instructions; and one or more hardware processors configured by the instructions to perform operations comprising:
accessing a particular place record from a data source, the particular place record describing a particular place on a geographic map;
generating a set of features for the particular place record based on a value from an attribute included in the particular place record;
processing the set of features using a classifier to generate a probability that the particular place record is associated with a class label; and
determining whether the particular place record is relevant based on at least the probability that the particular place record is associated with a class label.

Assignees

• Uber Technologies Inc

Inventors

• Yanez Livia Zarnescu
• Singh Shivendra Pratap
• Sheth Chandan
• Auyoung Alvin
• Yang Sheng
• Saxena Vikram

Classifications

• G06N5/022 Primary

  Knowledge engineering; Knowledge acquisition · CPC title

• G06N5/01

  Dynamic search techniques; Heuristics; Dynamic trees; Branch-and-bound · CPC title

• G06N7/01

  Probabilistic graphical models, e.g. probabilistic networks · CPC title

• G06N20/20

  Ensemble learning · CPC title

• G06F16/24578

  using ranking · CPC title