Swapnil R Kulkarni, 45554 Windlass Ln, Foster City, CA 94404

2021008, Mar 18, 2021

Jan 7, 2020

16/736621

- San Francisco CA, US
Alain Ducoulombier - Grenoble, FR
Swapnil Kulkarni - San Francisco CA, US
Alexander Lovell - San Francisco CA, US
Glenn Sorrentino - San Francisco CA, US

G06F 16/2453
G06F 16/23
G06F 16/242

Techniques are disclosed for classifying a user search query for a database system. In disclosed techniques, a computing system receives a user search query for the database system and determines, based on the user search query, a database query that is compatible with an interface of the database system to implement the user search query. In some embodiments, the computing system causes a query remediation interface to be presented to a user that entered the user search query. In some embodiments, the interface includes: a classification of the user search query that specifies attributes of the database query, and one or more elements selectable to alter the database query. The computing system receives, from the user via the query remediation interface, input for altering the database query and determines an updated database query based on the input. The computing system may access the database system using the updated database query.

2020009, Mar 26, 2020

Sep 26, 2018

16/143338

- San Francisco CA, US
Swapnil Sanjay Kulkarni - San Francisco CA, US

G06F 17/30

A system stores records of different entity types and processes search queries to determine search results comprising records that match the search query. The system receives a search query comprising search keywords from a source user. The system identifies a target user based on a search keyword received in the search query. The system determines a relationship between the source user and the target user. The system determines a relationship strength score for the relationship between the source user and the target user and ranks the search results based on the relationship strength score. The system provides the search results to the source user.

2020007, Mar 5, 2020

Aug 30, 2018

16/118410

- San Francisco CA, US
Swapnil Sanjay Kulkarni - San Francisco CA, US

G06F 17/30
G06N 3/04
G06N 3/08

A system stores records of different entity types and processes search queries to determine search results comprising records that match the search query. The system determines clusters of users based on feature vectors describing the users. A feature vector may be extracted from a hidden layer of a neural network. The system identifies a user that provided a search query and identifies a cluster of users matching the user. The system retrieves a set of weights for the cluster of users and uses the set of weights to rank the search results. The set of weights may represent relevance scores corresponding to various entity types. The system returns the ranked search results.

2019034, Nov 7, 2019

May 7, 2018

15/973377

- San Francisco CA, US
Swapnil Sanjay Kulkarni - San Francisco CA, US

G06F 17/30

A client device receives search queries and displays via a user interface, search results representing a set of the records based on the search queries. The client device monitors implicit user interactions with search query terms and records displayed in response to various search queries, for example, implicit user interactions representing movements of cursor on the portion of user interface displaying a particular record. The client device receives a partial search query. Partial search results representing a set of the records based on the partial search query are determined for display via the user interface. The relevance score for each record is determined based on implicit user interactions associated with past search queries. The partial search results are ranked based on the relevance scores and displayed by the client device according to the ranked order.

2019020, Jul 4, 2019

Oct 31, 2018

16/177334

- San Francisco CA, US
Swapnil Sanjay Kulkarni - San Francisco CA, US

G06F 17/30
H04L 29/08

A system stores objects of different types and processes search requests to determine search results matching the search criteria. For various objects stored in the system, the system tracks implicit user interactions and stores information of implicit user interactions. The implicit user interactions may be received in response to an object being presented as a search result or presented in response to other requests, for example, a request to browse objects or access the object otherwise. For each search result, the system determines a relevance score based on the stored information describing implicit user interactions. The relevance score of each entity type is used to rank search results for search requests. The system determines snippets for presenting to users along with search results based on implicit user interactions. The system also configures user interfaces for presenting search results based on implicit user interactions.

2019020, Jul 4, 2019

Dec 28, 2017

15/857613

- San Francisco CA, US
Swapnil Sanjay Kulkarni - San Francisco CA, US

G06F 17/30
H04L 29/08

A system stores objects of different types and allows search across the objects. The system receives search requests and processes them to determine search results matching the search criteria. For each of a plurality of search requests the system tracks implicit user interactions and stores information of implicit user interactions and associated search results and search requests. For each of a plurality of search results a relevance score is determined based on the stored information. The relevance score of each entity type is used to rank search results for search requests.