A device and method for providing recommended words for a character input by a user are provided. The method by which the device provides recommended words includes: receiving an input for inputting a character in a character input window; recommending at least one pseudo-morpheme including the input character by analyzing the input character; recommending at least one extended word including a selected pseudo-morpheme in response to receiving an input for selecting one of the at least one pseudo-morpheme; and displaying a selected extended word in response to receiving an input for selecting one of the at least one extended word.

A computer-implemented method, a computer program product, and a computer system for keyword extraction. A computer vectorizes word sets by splitting text in a corpus. The computer trains a Gaussian mixture distribution model for the word sets and obtains an inverse document frequency (IDF) value of a word set from the learned Gaussian mixture distribution model. The computer trains a Gaussian mixture distribution model for a cluster and obtains a term frequency (TF) value of the word set in the cluster from the learned Gaussian mixture distribution model. The computer calculates a term frequency-inverse document frequency (TF-IDF) value of the word set in the cluster, based on the TF value and the IDF value. The computer calculates TF-IDF values of the word sets in clusters and rearranges the word sets in a descending order of the TF-IDF values to obtain extracted keywords.

A computer-implemented method, a computer program product, and a computer system for keyword extraction. A computer vectorizes word sets by splitting text in a corpus. The computer trains a Gaussian mixture distribution model for the word sets and obtains an inverse document frequency (IDF) value of a word set from the learned Gaussian mixture distribution model. The computer trains a Gaussian mixture distribution model for a cluster and obtains a term frequency (TF) value of the word set in the cluster from the learned Gaussian mixture distribution model. The computer calculates a term frequency-inverse document frequency (TF-IDF) value of the word set in the cluster, based on the TF value and the IDF value. The computer calculates TF-IDF values of the word sets in clusters and rearranges the word sets in a descending order of the TF-IDF values to obtain extracted keywords.

An index generation method includes: executing an extraction process that includes extracting a plurality of morphemes from document information; and executing a generation process that includes generating index information with respect to each of the plurality of morphemes, wherein the index information includes a first logical value and a second logical value, wherein the first logical value indicates existence of a first morpheme associated with ‘morpheme information indicating the first morpheme’ and ‘position information indicating a position of the first morpheme in the document information’, and wherein the second logical value indicates existence of the first morpheme associated with ‘attribute information indicating a semantic attribute of the first morpheme’ and ‘position information indicating the position of the first morpheme’.

A method and apparatus with natural language processing is disclosed. The method includes determining a first similarity between an input sentence of a user and a select first database query sentence and dependent on a determination that the first similarity fails to meet a first threshold, determining a second similarity between a portion of the input sentence, less than all of the input sentence, and a select second database query sentence, and in response to the second similarity meeting a second threshold, outputting a response sentence corresponding to the second database query sentence as a response to the input sentence.

A method and apparatus with natural language processing is disclosed. The method includes determining a first similarity between an input sentence of a user and a select first database query sentence and dependent on a determination that the first similarity fails to meet a first threshold, determining a second similarity between a portion of the input sentence, less than all of the input sentence, and a select second database query sentence, and in response to the second similarity meeting a second threshold, outputting a response sentence corresponding to the second database query sentence as a response to the input sentence.

Provided is a word processing system which includes: a first generation unit which generates, based on sentence information including a plurality of sentences, hierarchy data indicating syntax tree data for each hierarchy with regard to each sentence; a second generation unit which acquires, from a plurality of hierarchy data generated by the first generation unit, hierarchy data of a second sentence similar to hierarchy data of a first sentence generated by the first generation unit, extracts a difference between the hierarchy data of the first sentence and the hierarchy data of the second sentence, and generates, as paraphrasing rule data, first expression data as a difference in the first sentence and second expression data as a difference in the second sentence; and a storage unit which stores the paraphrasing rule data generated by the second generation unit in a storage unit.

Introduced here are communication optimization platforms configured to improve comprehension, persuasion, or clarity of communications. Initially, a communication optimization platform can acquire input sample(s) that are associated with a source audience. The communication optimization platform can then create a linguistic profile for the source audience by examining the content of the input sample(s). Additionally or alternatively, the communication optimization platform may produce a psychographic profile that specifies various characteristics of the source audience, such as personality, opinions, attitudes, interests, etc. The communication optimization platform can then generate, based on the linguistic profile and/or the psychographic profile, affinity language for communicating with a target audience. By incorporating the affinity language into communications, the communication optimization platform can increase appeal to the target audience.

A device and method for providing recommended words for a character input by a user are provided. The method by which the device provides recommended words includes: receiving an input for inputting a character in a character input window; recommending at least one pseudo-morpheme including the input character by analyzing the input character; recommending at least one extended word including a selected pseudo-morpheme in response to receiving an input for selecting one of the at least one pseudo-morpheme; and displaying a selected extended word in response to receiving an input for selecting one of the at least one extended word.

A device and method for providing recommended words for a character input by a user are provided. The method by which the device provides recommended words includes: receiving an input for inputting a character in a character input window; recommending at least one pseudo-morpheme including the input character by analyzing the input character; recommending at least one extended word including a selected pseudo-morpheme in response to receiving an input for selecting one of the at least one pseudo-morpheme; and displaying a selected extended word in response to receiving an input for selecting one of the at least one extended word.