Intelligent selector control for user interfaces
Methods and systems for intelligently recommending selections for a selector control are disclosed. The method includes receiving a recommendation request from a selector control client, the recommendation request comprising a search string and a unique identifier of a user interacting with a selector control; identifying user identifiers of usernames matching the search string; retrieving machine learning features corresponding to the user identifiers of usernames matching the search string; applying a machine learning model to the retrieved machine learning features to assign weights to the retrieved machine learning features; computing recommendation scores for the user identifiers based on the assigned weights to the retrieved machine learning features; ranking the user identifiers based on the recommendation scores; and forwarding a ranked list of user identifiers to the selector control client for displaying in the selector control for selection by the user interacting with the selector control.
1 . A computer-implemented method comprising:
in response to receiving a text input with respect to a first selector control of a client application instantiated with respect to a user account having a unique identifier, generating a search query including the unique identifier and at least a portion of the text input;
providing the search query to a selector control system to obtain a set of entries;
providing the set of entries to a first ranking module associated with a first selector type of the first selector control to obtain a first set of recommendation scores;
generating a first set of ranked entries based on the set of entries and the first set of recommendation scores;
transmitting the first set of ranked entries to the first selector control, thereby causing the client application to display the first set of ranked entries;
in response to receiving the text input with respect to a second selector control of the client application different than the first selector control, providing the set of entries to a second ranking module associated with a second selector type of the second selector control to obtain a second set of recommendation scores;
generating a second set of ranked entries based on the set of entries and the second set of recommendation scores, the second set of ranked entries different than the first set of ranked entries; and
transmitting the second set of ranked entries to the second selector control, thereby causing the client application to display the second set of ranked entries.
2 . The computer-implemented method of claim 1 , wherein subsequent to transmitting the first set of ranked entries to the first selector control, the method comprises:
receiving a user selection of a particular entry of the first set of ranked entries;
generating a selection event record indicating the text input and the particular entry; and
retraining a machine learning model of the first ranking module associated with the first selector type using the selection event record.
3 . The computer-implemented method of claim 2 , wherein subsequent to retraining the machine learning model, the method further comprises:
receiving the text input with respect to the first selector control;
querying the first ranking module associated with the first selector type to obtain a third set of recommendation scores for the set of entries;
generating a third set of ranked entries based on the set of entries and the third set of recommendation scores, the third set of ranked entries having the particular entry promoted within the third set of ranked entries as compared to the first set of ranked entries; and
transmitting the third set of ranked entries to the first selector control, thereby causing the client application to display the third set of ranked entries.
4 . The computer-implemented method of claim 1 , wherein causing the client application to display at least one of the first set of ranked entries or the second set of ranked entries includes selecting a subset of at least one of the first set of ranked entries or the second set of ranked entries in accordance with a predefined maximum number of results.
5 . The computer-implemented method of claim 4 , wherein prior to causing display of the first set of ranked entries or the second set of ranked entries, the method further comprises determining the predefined maximum number of results based on a number of recommendation scores within at least one of the first set of recommendation scores or the second set of recommendation scores meeting a minimum threshold recommendation score.
6 . The computer-implemented method of claim 1 , wherein each of the first selector type and the second selector type is at least one of an assignee type, a mention type, or a generic type.
7 . The computer-implemented method of claim 1 , further comprising:
in response to receiving a selection of a particular entry from at least one of the first set of ranked entries or the second set of ranked entries, generating a notification; and
transmitting the notification to a particular user device associated with the particular entry.
8 . A computer-implemented method comprising:
in response to receiving a text input with respect to a first selector control of a client application instantiated with respect to a user account, generating a search query including at least a portion of the text input;
providing the search query to a selector control system to obtain a set of entries;
providing the set of entries to a first machine learning model of a ranking module, the first machine learning model associated with a first selector type of the first selector control, to obtain a first set of recommendation scores;
generating a first set of ranked entries based on the set of entries and the first set of recommendation scores;
transmitting the first set of ranked entries to the client application, thereby causing the client application to display the first set of ranked entries with respect to the first selector control;
in response to receiving the text input with respect to a second selector control of the client application different than the first selector control, providing the set of entries to a second machine learning model of the ranking module, the second machine learning model associated with a second selector type of the second selector control, to obtain a second set of recommendation scores;
generating a second set of ranked entries based on the set of entries and the second set of recommendation scores, the second set of ranked entries different than the first set of ranked entries; and
transmitting the second set of ranked entries to the client application, thereby causing the client application to display the second set of ranked entries with respect to the second selector control.
9 . The computer-implemented method of claim 8 , wherein:
the client application is an issue tracking application comprising an issue view interface;
the issue view interface includes the first selector control and the second selector control, wherein the first selector control is an assignee selector control and the second selector control is a mention selector control.
10 . The computer-implemented method of claim 9 , wherein the assignee selector control is displayed with respect to one or more particular issues of the issue view interface; and
in response to receiving a user selection of a particular entry in the first set of ranked entries, assigning the one or more particular issues to a particular user account corresponding to the particular entry.
11 . The computer-implemented method of claim 9 , wherein the mention selector control is displayed proximate to a comment editor region for a particular issue of the issue view interface; and
in response to receiving a user selection of a particular entry in the second set of ranked entries, inserting a mention for a particular user account corresponding to the particular entry in the comment editor region.
12 . The computer-implemented method of claim 11 , wherein subsequent to inserting the mention for the particular user account, the method further comprises:
identifying a particular user device associated with the particular user account corresponding to the particular entry;
generating a notification indicating the particular issue; and
transmitting the notification to the particular user device associated with the particular user account.
13 . The computer-implemented method of claim 8 , wherein subsequent to transmitting the first set of ranked entries to the first selector control, the method comprises:
receiving a user selection of a particular entry of the first set of ranked entries;
generating a selection event record indicating the text input and the particular entry; and
retraining the first machine learning model using the selection event record.
14 . The computer-implemented method of claim 8 , wherein:
the first machine learning model corresponds to a first set of features comprising at least one of:
a comment feature; and
an edit feature; and
the second machine learning model corresponds to a second set of features comprising at least one of:
a mention feature; and
a mentionee feature.
15 . A computer processing system comprising:
one or more processing units;
one or more communication interfaces; and
a non-transitory computer-readable storage medium storing sequences of instructions, which when executed by the one or more processing units, cause the one or more processing units to:
cause instantiation of a client application of a product platform with respect to a user account having a unique identifier;
cause display, within the client application, of a user interface comprising a first selector control and a second selector control;
in response to receiving a text input via the first selector control:
provide at least a portion of the text input to a selector control system to obtain a set of entries;
provide the set of entries to a first machine learning model associated with a first selector type of the first selector control to obtain a first set of recommendation scores; and
generate a first set of ranked entries based on the set of entries and the first set of recommendation scores;
cause display, within a first selection menu of the user interface, of the first set of ranked entries;
in response to receiving the text input via the second selector control:
provide the set of entries to a second machine learning model associated with a second selector type of the second selector control to obtain a second set of recommendation scores;
generate a second set of ranked entries based on the set of entries and the second set of recommendation scores, the second set of ranked entries different from the first set of ranked entries; and
cause display, within a second selection menu of the user interface, the second set of ranked entries.
16 . The computer processing system of claim 15 , wherein:
the first selector control is an assignee selector control displayed proximate to a content item of the user interface; and
the first selection menu is a dropdown menu of the first selector control.
17 . The computer processing system of claim 16 , wherein:
the second selector control is a mention selector control displayed proximate to the content item of the user interface; and
the second selection menu is a dropdown menu of the second selector control.
18 . The computer processing system of claim 15 , wherein the sequences of instructions, when executed by the one or more processing units, further cause the one or more processing units to:
receive a user selection of a particular entry of at least one of the first set of ranked entries or the second set of ranked entries; and
retrain at least one of the first machine learning model or the second machine learning model using the particular entry.
19 . The computer processing system of claim 15 , wherein the first set of ranked entries and the second set of ranked entries are displayed in accordance with a predefined maximum number of results.
20 . The computer processing system of claim 15 , wherein:
each entry of the first set of ranked entries corresponds to a respective avatar icon; and
each entry of the first set of ranked entries is displayed within a respective selectable element including the respective avatar icon.