Abstract: The present disclosure provides a computer-implemented method for scoring and visualizing combined search results, comprising: (a) performing a plurality of individual searches on data objects stored in a database, wherein the data objects are stored in defined fixed data structures; (b) combining the plurality of individual searches into a combined search; (c) determining a weight for each of the individual searches; and (d) obtaining a search result of the combined search, wherein the search result of the combined search comprises scores associated with a subset of the data objects.

Abstract: The present disclosure provides a computer-implemented method for scoring and visualizing combined search results, comprising: (a) performing a plurality of individual searches on data objects stored in a database, wherein the data objects are stored in defined fixed data structures; (b) combining the plurality of individual searches into a combined search; (c) determining a weight for each of the individual searches; and (d) obtaining a search result of the combined search, wherein the search result of the combined search comprises scores associated with a subset of the data objects.

Abstract: The present disclosure provides systems and methods for end-to-end machine learning. A method of the present disclosure may comprise one or more operations of data ingestion, data preparation, feature storage, model building, and productionizing by the model. The methods and systems of the present disclosure may use an Automated Machine Learning (AutoML) algorithm and eXplainable Artificial Intelligence (XAI).

Abstract: The present disclosure provides a computer-implemented method for applying an analysis to a data model comprising data objects. The method may comprise receiving the analysis and the first data model each in semantic format. Next, the analysis and the data model may be computer processed to (i) identify one or more elements missing from the data model and (ii) determine that the analysis is not applicable to the data model upon identification of the one or more elements. The one or more elements may then be presented to a user for adjusting the data model. This may be repeated until the analysis is applicable to the data model. The analysis may then be performed on the data objects of the data model.

Abstract: The present disclosure provides a computer-implemented method for applying an analysis to a data model comprising data objects. The method may comprise receiving the analysis and the first data model each in semantic format. Next, the analysis and the data model may be computer processed to (i) identify one or more elements missing from the data model and (ii) determine that the analysis is not applicable to the data model upon identification of the one or more elements. The one or more elements may then be presented to a user for adjusting the data model. This may be repeated until the analysis is applicable to the data model. The analysis may then be performed on the data objects of the data model.

Abstract: The present disclosure provides a computer-implemented method for scoring and visualizing combined search results, comprising: (a) performing a plurality of individual searches on data objects stored in a database, wherein the data objects are stored in defined fixed data structures; (b) combining the plurality of individual searches into a combined search; (c) determining a weight for each of the individual searches; and (d) obtaining a search result of the combined search, wherein the search result of the combined search comprises scores associated with a subset of the data objects.

Abstract: The present disclosure provides a computer-implemented method for applying an analysis to a data model comprising data objects. The method may comprise receiving the analysis and the first data model each in semantic format. Next, the analysis and the data model may be computer processed to (i) identify one or more elements missing from the data model and (ii) determine that the analysis is not applicable to the data model upon identification of the one or more elements. The one or more elements may then be presented to a user for adjusting the data model. This may be repeated until the analysis is applicable to the data model. The analysis may then be performed on the data objects of the data model.