Abstract: An input/output of a system receives an electronic file comprising text. A processor of the system identifies keywords in the text. The processor correlates the keywords to music attributes and matches the music attributes to musical works. The processor determines computer network locations of the musical works. The processor also adds links to the network locations of the musical works to the electronic file to create a music-enhanced electronic file. The input/output outputs the music-enhanced electronic file that now contains the links to the musical works.

Abstract: The present disclosure determines whether or not a character string of a result obtained by a character recognition process matches a word of a word dictionary; and when a pattern that is similar to a predefined arrangement pattern of a character type is present in the character string of the result obtained by the character recognition process that is determined not to match a word of the word dictionary, changes the character recognition process for the character string based on the pattern.

Abstract: Devices and techniques are generally described for determining named entity recognition tags. In various examples, first input data representing a natural language input may be determined. In some examples, a first machine learned model may determine first data comprising a first encoded representation of the first input data. In various examples, second data representing a grouping of text of the first input data may be determined based at least in part on the first data. In some examples, first entity data may be determined by searching a memory layer using the second data. In at least some examples, the first entity data and the first data may be combined to generate third data. In various examples, output data comprising a predicted named entity recognition tag may be generated for the grouping of text based at least in part on the third data.

Abstract: Methods for generating content summaries in a web content management service, wherein in one embodiment a digital page editor and a component browser are launched to enable selection of a first content item. A summary of the first content item is automatically generated according to parameters that may have default values or values set by a user. The parameters may specify a size for the summary as a percentage of the first content item's size, as a particular number of lines, characters or words, as a size for a particular type of device, etc. The automatically generated summary is provided to the digital page editor, which can edit it and add it to the digital page. The summary is stored in a content repository as an independent summary content item with its own metadata.

Abstract: As described herein, a system for expanding contractions in electronically stored text includes expanding contractions having only on expanded form. For remaining contractions, a grammar check is performed for all possible expanded forms to determine if an expanded form can be selected based on context and grammar rules. If an expanded form is not evident from the first two steps, all possible expanded forms of the remaining contractions are converted to a vector representation along with the original text. A Word Movers Distance (WMD) for each possible expansion is calculated using the vectors for each possible expansion and the original text. An expanded form is chosen without human intervention based on the grammar score alone or the WMD and the grammar score.

Abstract: A computer adjusts digital content to match a user language proficiency level. The computer receives digital content including words and monitors word consumption activity of a user. The computer identifies troublesome words associated with content consumption delays and establishing a user language proficiency level based on a difficulty value associated with said troublesome words. The computer identifies content words having difficulty level above the language proficiency level. The computer identifies from a word corpus, exchange candidate words having a difficulty level equal to or below said language proficiency level. The computer generates using a natural language processing (NLP) algorithm, word embeddings for said target words and said exchange candidate words. The computer selects from the exchange candidate words, replacement words having word embeddings substantially the same as the word embeddings of said target words.

Abstract: A collaborative matter management and analysis tool is presented. Each matter has its own workspace that is built around a collaborative backbone. Users can provide access to the matter workspace to anyone who they want to collaborate with, including others at their organization and persons outside the organization, such as clients, lawyers, experts, vendors and other third parties. Processing of the document is automatic and based on the content and document type. The document, when uploaded, is OCR'd and based on the content, citations are converted to hyperlinks and the cited documents are linked. Documents and events are associated to enable enhanced productivity tools such as searching and e-brief.

Abstract: A method including isolating a protocol language of a data set comprising a text structure representing data regarding a network communication procedure between a plurality of user devices, wherein the protocol language comprises a pattern for implementing the network communication procedure; generating a document from the data set, wherein the document includes a text structure, organizing, in light of the protocol language, the text structure into a natural language scheme; and detecting, using the natural language scheme, insights in the document.

Abstract: A user requests explanation of a term. In response, a definition is provided. The user can indicate that the user does not understand a new term included in the definition. In response, explanation information is customized based on analysis of the initial term and the new term, and then the explanation information is provided to the user.

Abstract: Aspects of the present disclosure relate to modularizing and embedding modules across a variety of web applications. More specifically, the present disclosure provides an adaptive UI module to web application servers that adapts its format upon evaluating an environment of the web application and receiving a user request for supplemental information. For example, a single adaptive UI module may be used across a variety of web applications, with a variety of requests for supplemental content from within each web application, to generate multiple, unique formatted UI modules. In this way, a single adaptive UI module may generate formatted UI modules specific to the formatting requirements of each requesting web application, with supplemental content related to each unique user request from within each web application.

Abstract: Techniques to capture document data are disclosed. It is determined that a sequence of pages in a stream of document page images comprise a single multi-page document. Data is extracted from two or more different pages included in the sequence. The data extracted from two or more different pages included in the sequence of pages is used to populate a data entry form associated with the multi-page document.

Abstract: A computer-implemented technique for characterizing lexical concreteness in narrative includes receiving data encapsulating narrative text having a plurality of words. Thereafter, the function words can be removed from the narrative text to result in only content words. A concreteness score can then be assigned to each content word by polling a database to identify matching words and to use concreteness scores associated with such matching words as specified by the database. Data can then be provided which characterizes the assigned concreteness scores. Related apparatus, systems, techniques and articles are also described.

Abstract: Upon closing and/or saving a file, a user may view changes made to the file.

Abstract: Systems and methods for delivering cross-site auto-play media are described herein. The server can receive, from a client device, a request for media content at a first domain embedded in a content element from a second domain. The request can include an identifier indicating that the client device is configured to restrict cross-domain redirection. The server can determine, responsive to identifying the identifier indicating that the client device is configured to restrict cross-domain redirection, that the request comprises a content type header having a first predetermined value. The server can generate, responsive to the determination, a response comprising the media content element in a body of the response. The server can transmit the response to the client device. Receipt of the response can cause the client device to extract the media content element from the body of the response and to render the media content element.

Abstract: In some embodiments, a method includes identifying a set of word bounding boxes in a first electronic document, and identifying locations of horizontal white space between two adjacent rows from a set of rows in a table. The method includes determining, using a Natural Language Processing algorithm, an entity name from a set of entity names for each table cell from a set of table cells in the table. The method includes determining, using a machine learning algorithm a class from a set of classes for each row from the set of rows. The method includes extracting a set of table cell values associated with the set of table cells, and generating a second electronic document including the set of table cell values arranged in the set of rows and the set of columns such that the set of words in the table are computer-readable in the second electronic document.

Abstract: A computer-implemented method is described. The method includes a computing system receiving a first voice input from a user for generating a bookmark. Responsive to receiving the voice input, the computing system obtains a resource identifier associated with a resource page. The method includes the computing system storing the resource identifier as a bookmark in a bookmark index that is accessible in response to a request from a user device. The method further includes the computing system using the resource identifier, stored as the bookmark, to access the resource page. The computing system uses the resource identifier to access the resource page based on the request from the user device. The request is generated by the user device in response to the user device receiving a second voice input from the user.

Abstract: This disclosure relates to methods, non-transitory computer readable media, and systems that use machine-learning techniques to facilitate the creation, timing of distribution, or follow-up actions for digital surveys. In one such implementation, the disclosed methods, non-transitory computer readable media, and systems use a survey-creation-machine learner to generate suggested survey questions for an administrator designing a digital survey. Additionally, in some implementations, the disclosed methods, non-transitory computer readable media, and systems use specialized machine learners to suggest timeframes in which to send digital surveys or to suggest action items to follow up on responses to the survey questions.

Abstract: The embodiments of the present disclosure relate generally to techniques for identifying elements in a user interface (UI), and more particularly, techniques for determining UI elements selected on a contact-sensitive user interface and using those techniques to provide one or more haptic responses.

Abstract: Techniques for automated suggestions for cross-context digital item containers and collaboration are provided, including analyzing digital items in each of multiple portfolios of digital items in order to determine similarities among the portfolios. The techniques proceed by determining similar portfolios for a first portfolio of digital items, and suggesting changes (e.g., additions, deletions, or alterations of digital items) based on differences between the first portfolio and the similar ones. Those changes can be accepted or rejected and applied to the first portfolio of digital items.

Abstract: Systems and processes for word prediction using multiple contexts are provided. For example, a plurality of words are received. A first word context including a first plurality of received words, and a second word context corresponding to the first plurality of received words and a second plurality of received words, are obtained. A first current word probability is determined based on a first language model using the first word context. A second current word probability is determined based on a second language model using the second word context. A third current word probability is determined based on the second language model using the first word context. A fourth current word probability is determined based on the first current word probability, the second current word probability, and the third current word probability. An output is provided, to a user, including a current word prediction based on the fourth current word probability.