Abstract: A method of generating an instruction performance skeleton employs an instruction unit configured to receive a natural language instruction. From the natural language instruction, a sequence of clauses may be extracted. The instruction unit then determines a target website or websites on which to perform the task. The object models of the target website are generated. A comparison of the sequence of actions to the object model and its labelling hierarchical class structure is performed. Based on this comparison, an instruction performance skeleton is generated. In future, on the basis of a further natural language instruction that is similar to the previous natural language instruction, the instruction performance skeleton may be modified to generate a playback performance skeleton to arrange performance of a task.

Abstract: A method of executing a sequence of tasks includes receiving a natural language input indicative of the sequence of tasks. The natural language input may include a first task and a plurality of possible next tasks for the first task. The tasks may each be associated with a playback performance skeleton, indicative of a series of actions to be carried out on a web page. The series of action may have been generated, ahead of time, from a recorded performance of a similar task. The first task may be arranged to be performed. Then, based on a result of the performance of the first task, a successive task from among a plurality of possible next tasks associated with the result of performance of the first task may be selected. The successive task may then be arranged to be performed.

Abstract: A system and method uses a vectorization model to determine similar elements within a web page to the known web page. The vectorization model takes a known web element and generates a first set of vectors, representative of the various properties of the web element. A vectorization model generates a second set of vectors for each element in a new web page. The first set of vectors is compared to each second set of vectors for each element in the new web page to select the most similar web element.

Abstract: A system and method for automating a task on a web page. The system and method include a recording engine, wherein a user can record a new task. Based on template matching, the system and method can be used to generate a model for carrying out the task on a new website. Based on a natural language input, the system can determine the task, specifics for implementing the task, and the web page or web pages to carry out the task on.

Abstract: Embodiments described herein relate generally to content analysis technologies and natural language processing (NLP). In particular, devices, systems, and methods may implement a reverse sentence reconstruct (RSR) utility, and a sentence vectorization technique (SVT) utility. A computer server may be configured to receive a feeling classification request with text data elements, and in response, generate a feeling classification response indicating feeling for the text data elements using the RSR utility and the SVT utility.

Abstract: Embodiments described herein relate generally to content analysis technologies and natural language processing (NLP). In particular, devices, systems, and methods may implement a reverse sentence reconstruct (RSR) utility, and a sentence vectorization technique (SVT) utility. A computer server may be configured to receive a feeling classification request with text data elements, and in response, generate a feeling classification response indicating feeling for the text data elements using the RSR utility and the SVT utility.