The application discloses a method and device for personalized search of visual media. Semantic analysis is conducted on a visual media query text of a user to obtain visual semantic information, time information and/or location information. Semantic similarity matching is conducted on a result of the semantic analysis and attribute data of each visual medium within a specified search range to obtain a query similarity of the visual medium. The visual medium is an image or a video, and the attribute data include personalized visual semantic information, personalized time information and/or personalized location information. A corresponding visual media query result is generated based on the query similarity. By adopting the application, users are provided with visual media which is a result of a personalized.

Methods, systems, and devices for automatically converting a static electronic file format and its various elements into a dynamic digital form with executable elements that can be customized before being used. The resulting digital form is compatible with digital workflows and processes. The disclosed systems, methods, and devices go beyond simply extracting data from the original electronic file format and instead enable users to, without using code, convert the source form into a dynamic, malleable digital form while still retaining the source form's original purpose and functionality.

A client device processing received emoji messages using emoji-first messaging. Text messaging is automatically converted to emojis by an emoji-first application so that only emojis are communicated from one client device to another client device. Each client device has a library of emojis that are mapped to words, which libraries are customizable and unique to the users of the client devices, such that the users can communicate secretly in code. Upon receipt of a string of emojis, a user can select the emoji string to convert to text if desired, for a predetermined period of time.

The field of the invention relates to systems and methods for creating on-line transactional statements, and more particularly to creating electronic transactional statements that can responsively and dynamically fit any display window size. In an embodiment, a responsive transactional statement generation system having one or more processors and a non-transitory computer-readable medium containing program instructions that cause said one or more processors to receive data files each includes data representing one or more transactional statements, parse the received data files using one or more predetermined schemas to create restructured electronic transactional statements, save the restructured electronic transactional statements and display the restructured electronic transactional statements responsively at a user device. In other embodiments, the responsive transactional statement generation system compresses the restructured electronic transactional statements, saves the restructured electronic transactional statements in a secure format, and uses predetermined quality assurance processes.

The present disclosure includes systems, apparatuses, and methods for event identification. In some aspects, a method includes receiving data including text and performing natural language processing on the received data to generate processed data that indicates one or more sentences. The method also includes generating, based on a first keyword set, a second keyword set having more keywords than the first keyword set. The method further includes, for each of the first and second keyword sets: detecting one or more keywords and one or more entities included in the processed data, determining one or more matched pairs based on the detected keywords and entities, and extracting a sentence, such as a single sentence or multiple sentences, from a document based on the one or more sentences indicated by the processed data. The method may also include outputting at least one extracted sentence.

The present disclosure includes systems, apparatuses, and methods for event identification. In some aspects, a method includes receiving data including text and performing natural language processing on the received data to generate processed data that indicates one or more sentences. The method also includes generating, based on a first keyword set, a second keyword set having more keywords than the first keyword set. The method further includes, for each of the first and second keyword sets: detecting one or more keywords and one or more entities included in the processed data, determining one or more matched pairs based on the detected keywords and entities, and extracting a sentence, such as a single sentence or multiple sentences, from a document based on the one or more sentences indicated by the processed data. The method may also include outputting at least one extracted sentence.

System and methods (100) for automatically tagging electronic documents are disclosed. An input module receives (102) an electronic document to be tagged. A preprocessing module then preprocesses (104) the electronic document to be tagged. The preprocessing of the electronic document comprises extracting a text from the electronic document to be tagged, replacing a number or a date in the extracted text with a predetermined symbol, and tokenizing the extracted text with the predetermined symbol into a plurality of tokens. After the preprocessing (104), a deep learning module determines (106) a tag for at least one of the plurality of tokens. The determined tag for the at least one token is then output (108) by an output module.

System and methods (100) for automatically tagging electronic documents are disclosed. An input module receives (102) an electronic document to be tagged. A preprocessing module then preprocesses (104) the electronic document to be tagged. The preprocessing of the electronic document comprises extracting a text from the electronic document to be tagged, replacing a number or a date in the extracted text with a predetermined symbol, and tokenizing the extracted text with the predetermined symbol into a plurality of tokens. After the preprocessing (104), a deep learning module determines (106) a tag for at least one of the plurality of tokens. The determined tag for the at least one token is then output (108) by an output module.

The present invention relates to a system for converting a rich text document into an active document suitable for consumption on a particular device system, or operating system by human or machine. The system comprises a server including a non-transitory non-volatile storage medium. The non-transitory non-volatile storage medium is adapted to store at least rich text documents and active documents that have been converted from a rich text document format into an active document format. The server is adapted to carry out the steps of: scanning and parsing the rich text document to extract structural elements and contents; scanning and parsing the rich text document to extract embedded metadata; connecting structural elements and contents with the extracted metadata and the rich document to form a render data set; and sending the render data set to a configurable render module that outputs at least one active document.

The present invention relates to a system for converting a rich text document into an active document suitable for consumption on a particular device system, or operating system by human or machine. The system comprises a server including a non-transitory non-volatile storage medium. The non-transitory non-volatile storage medium is adapted to store at least rich text documents and active documents that have been converted from a rich text document format into an active document format. The server is adapted to carry out the steps of: scanning and parsing the rich text document to extract structural elements and contents; scanning and parsing the rich text document to extract embedded metadata; connecting structural elements and contents with the extracted metadata and the rich document to form a render data set; and sending the render data set to a configurable render module that outputs at least one active document.