Abstract: A method includes receiving, at one or more processors, input indicating selection of a data field of a plurality of data records. The method also includes, responsive to the selection, performing, by the one or more processors, a clustering operation to generate clusters based on semantic similarity of text content of the data field in the plurality of data records. The method further includes filtering, by the one or more processors, the plurality of data records based on the clusters to generate filtered data records and generating output representing the filtered data records.

Abstract: A method of generating a searchable representation of an electronic document includes obtaining an electronic document specifying a graphical layout of content items including text. The method also includes determining pixel data representing the graphical layout of the content items and providing input data based, at least in part, on the pixel data to a document parsing model. The document parsing model is trained to detect functional regions within the graphical layout based on the input data, assign boundaries to the functional regions based on the input data, and assign a category label to each functional region that is detected. The method also includes matching portions of the text to corresponding functional regions based on the boundaries assigned to the functional regions and locations associated with the portions of the text and storing data representing the content items, the functional regions, and the category labels in a searchable data structure.

Abstract: A device includes a processor configured to receive first user input indicating keywords of a search and to select matching document segments and exploratory document segments from a document set. Each document segment of the matching document segments is selected in response to determining that the document segment matches at least one of the keywords. Each document segment of the exploratory document segments does not match any of the keywords. The processor is further configured to display first search results indicating at least one of the matching document segments and at least one of the exploratory document segments, and to receive second user input indicating whether the first search results are relevant to the search. The processor is configured to generate a search model based on the second user input, and to generate second search results based at least in part on applying the search model to the document set.

Abstract: A method of generating a searchable representation of an electronic document includes obtaining an electronic document specifying a graphical layout of content items including text. The method also includes determining pixel data representing the graphical layout of the content items and providing input data based, at least in part, on the pixel data to a document parsing model. The document parsing model is trained to detect functional regions within the graphical layout based on the input data, assign boundaries to the functional regions based on the input data, and assign a category label to each functional region that is detected. The method also includes matching portions of the text to corresponding functional regions based on the boundaries assigned to the functional regions and locations associated with the portions of the text and storing data representing the content items, the functional regions, and the category labels in a searchable data structure.

Abstract: A method includes receiving input designating a term of interest in a document of a document corpus and determining a target context embedding representing a target word group that includes the term of interest and context words located in the document proximate to the term of interest. The method also includes identifying, from among the document corpus, a first candidate word group that is semantically similar to the target word group and a second candidate word group that is semantically dissimilar to the target word group. The method further includes receiving user input identifying at least a portion of the first candidate word group as associated with a first label and identifying at least a portion of the second candidate word group as not associated with the first label. The method also includes generating labeled training data based on the user input to train a text classifier.