The present disclosure relates to systems and methods for matching electronic activities with record objects based on entity relationships. The method can include accessing a plurality of electronic activities, identifying an electronic activity, identifying a first participant associated with a first entity and a second participant associated with a second entity, determining whether a record object identifier is included in the electronic activity, identifying a first record object of the system of record that includes an instance of the record object identifier, and storing an association between the electronic activity and the first record object. The method can include determining a second record object corresponding to the second entity, identifying, using a matching policy, a third record object linked to the second record object and identifying a third entity, and storing, by the one or more processors, an association between the electronic activity and the third record object.

Techniques for building a machine learning framework with tracking, model building and maintenance, and feedback loop are provided. In one technique, a prediction model is generated based on features of multiple entities. For each entity indicated in a first database, multiple feature values are identified, which include feature values stored in the first database and feature values based on sub-entity data regarding individuals associated with the entity. The feature values are input into the prediction model to generate a score for the entity. Based on the score, a determination is made whether to add, to a second database, a record for that entity. The second database is analyzed to identify other entities. For each such entity, a determination is made whether to generate a training instance; if so, a training instance is generated and added to training data, which is used to generate another prediction model.

Techniques for improved data services are provided. Upon receiving a first request from a first client, a first timeline comprising a first plurality of events for an asset indicated in the first request is generated. Upon receiving a second request from a second client, a second timeline comprising a second plurality of events is generated. A first submission for the asset is provided to the first client, comprising updating a first graphical user interface (GUI) output on a first device of the first client. Upon determining that the first client approved the first submission, a merged timeline is generated based on the first and second timelines, where the merged timeline includes the first and second pluralities of events, comprising: updating the first GUI output on the first device, and a second GUI output on a second device of the second client, to indicate the merged timeline.

Techniques for improved data services are provided. Upon receiving a first request from a first client, a first timeline comprising a first plurality of events for an asset indicated in the first request is generated. Upon receiving a second request from a second client, a second timeline comprising a second plurality of events is generated. A first submission for the asset is provided to the first client, comprising updating a first graphical user interface (GUI) output on a first device of the first client. Upon determining that the first client approved the first submission, a merged timeline is generated based on the first and second timelines, where the merged timeline includes the first and second pluralities of events, comprising: updating the first GUI output on the first device, and a second GUI output on a second device of the second client, to indicate the merged timeline.

Data analytics systems and methods are disclosed herein. A parser can parse reference data from various data sources to store in a data structure. An uploader can receive study data designated by a researcher and store the study data in the data structure. A matcher can compare analyte nameset data in the study data with analyte nameset data from the reference data to generate one or more links each correlating an instance of an analyte in the study data with an instance of that analyte in the reference data. Library overlays each include one or more modules to access reference data to generate organized associations of reference data. A calculation engine can receive a selection of one or more library overlay(s) and manipulate the reference data and study data according to the organized associations of the selected library overlay(s) to generate configured data stored in a collection of data caches for presentation to a researcher via a user interface.

Computer implemented systems and methods are disclosed for extracting specific data using machine learning algorithms. In accordance with some embodiments, a memory device that stores at least a set of computer executable instructions for a machine learning algorithm and a pre-fill engine; and at least one processor that executes the instructions that cause the pre-fill engine to perform functions that include: receiving electronic documents, seed dataset documents, and pre-fill questions; determining output data that enable navigation through the electronic documents using the machine learning algorithm; determining output questions that enable navigation through the electronic documents using the machine learning algorithm; determining output documents to enable navigation through the electronic documents using the machine learning algorithm; and presenting one or more answers for one or more of the output questions using a graphical user interface.

Exemplary embodiments relate to a system for recovering a conversation between a user and the system when the system is unable to properly respond to a user's input. The system may process the user input and determine an error condition exists. The system may query one or more storage systems to identify candidate text data based on their semantic similarity to the user input. The storage systems may store data related to past frequently entered inputs and/or user-generated inputs. Alternative text data is selected from the candidate text data, and presented to the user for confirmation.

Systems, devices, and methods of the present invention create a searchable index that includes informative portions of text. In an example, a computer-implemented method creates a discourse tree from a body of text. For each non-terminal node in the discourse tree, the method identifies a rhetorical relationship associated with the non-terminal node. The method labels each terminal node associated with the non-terminal node as either a nucleus or a satellite. The method further accesses a rule associated with the rhetorical relationship, and selects, based on the rule, selects the fragment associated with the nucleus. The method creates a searchable index including the selected fragments.

The present teaching relates to providing a query suggestion. In one example, a request is received for query suggestions with respect to a query prefix input by a user. A plurality of query suggestions is determined based on the query prefix and a preceding query input by the user. A degree of popularity of the preceding query is determined. One or more query suggestions are selected from the plurality of query suggestions based on the degree of popularity of the preceding query. The one or more query suggestions are provided as a response to the request.

The present teaching relates to providing a query suggestion. In one example, a request is received for query suggestions with respect to a query prefix input by a user. A plurality of query suggestions is determined based on the query prefix and a preceding query input by the user. A degree of popularity of the preceding query is determined. One or more query suggestions are selected from the plurality of query suggestions based on the degree of popularity of the preceding query. The one or more query suggestions are provided as a response to the request.