Abstract: Systems and methods for providing data protection operations including cyber-threat protection operations. A sentiment analysis may be performed using language analysis to identify or determine a general or specific sentiment with or without intent to do harm. A score of the sentiment is then determined to assess risk. The data backup policy can be updated based on the assessed risk.

Abstract: A document processing device includes: an input unit for receiving an input question sentence; a text analysis unit for performing a morphological analysis on a sentence received by the input unit; a hypothetical question storage unit for storing a hypothetical question sentence and an answer sentence in association with each other; a search unit for searching for the hypothetical question sentence similar to the input question sentence from the hypothetical question storage unit and obtaining an answer sentence; an output unit for outputting the answer sentence; and a normalization processing unit for performing a normalization on each word of the input question sentence and the hypothetical question sentence converted into word strings by the text analysis unit. The search unit is configured to perform a similarity determination on the input question sentence and the hypothetical question sentence whose words are normalized by the normalization processing unit.

Abstract: The present disclosure provides a method and apparatus for determining an extended reading content, a device, and a storage medium, relating to the field of data processing. The method may include: displaying a target page, in response to a viewing request to the target page; giving a reading prompt to an extended reading resource in the target page, based on a corresponding relationship between a requirement recognition result of at least one target reading content in the target page and the extended reading resource; and displaying the extended reading resource, in response to the viewing request matching the reading prompt.

Abstract: Embodiments include methods, systems and computer program products for performing named entity recognition. Aspects include obtaining a text having a plurality of words and comparing each of the plurality of words to a dictionary. Aspects also include creating, based on the comparison, an annotation for at least one of the plurality of words that the least one of the plurality of words refers to a named entity. Aspects further include parsing the text to identify a part of speech for each of the plurality of words and removing the annotations from each of the at least one of the plurality of words that has a part of speech that is not one or a noun and a noun supporting adjective.

Abstract: Embodiments of the present disclosure provide methods and apparatus for outputting information. The method may include: obtaining a sentence to be identified; Performing word segmentation on the to be identified sentence to obtain a word sequence; Inputting a word sequence into a pre-trained multi-task element recognition model based on sequence labeling and entity word prediction, and outputting the identified entity words, entity categories and entity word positions, where the multi-task element recognition model includes a sequence labeling network for performing sequence labeling tasks and an entity word predicting network for performing entity word predicting task, and the sequence labeling network is fused with the entity word predicting network through a fusion module.

Abstract: Methods, systems, and computing devices for visualizing natural language processing algorithm processes are described herein. A plurality of categories may be determined. Each color of a plurality of colors may correspond to the categories. Text content may be processed using a natural language processing algorithm. Confidence values indicating, for each of a plurality of portions of the text content, a degree of confidence corresponding to one or more of the plurality of categories may be determined. Display colors may be determined based on the confidence values. A user interface comprising a visualization of the text content may be displayed, and the user interface may be configured to show each portion of the text content using a display color such that the user interface indicates changes in confidence across the plurality of characters.

Abstract: A learning support device stores, as execution information, a set of an input value, an execution output value as an execution result and an expected output value, for a machine learning program. An arithmetic device generates an output value different from the expected output value as a teacher output value in accordance with a predetermined rule when the execution output value and the expected output value for a predetermined input value match each other, generates a loss function based on a difference between the teacher output value and the execution output value, generates a change value indicating a change in the loss function for each parameter in the neural network, calculates an influence degree of predetermined learning by calculating influence of an update value of the parameter obtained by the learning on the change value, and determines whether or not the update value is adopted based on the influence degree.

Abstract: Embodiments for analyzing language content are provided. An ambiguous sentence is identified. A first word and a second word within the ambiguous sentence are selected. At least one synonym outlier for the first word and at least one synonym outlier for the second word are determined. A phrase is generated utilizing the at least one synonym outlier for the first word and the at least one synonym outlier for the second word. A context for the ambiguous sentence is determined based on the generated phrase.

Abstract: Systems and techniques for an artificial intelligence natural language processing platform are described herein. A first dialogue configuration ruleset may be obtained for a first intent for a first entity. First user input may be received that includes a first text string from a chatbot session. The first intent may be identified from the chatbot session through evaluation of the first text string by a natural language processing engine using the first dialogue configuration ruleset. A dialogue stack may be generated for the chatbot session that includes a first state based on the first dialogue configuration ruleset. A first response to the first user input may be displayed based on the first dialogue configuration ruleset. The dialogue stack may be updated based on the first response.

Abstract: In some embodiments, a method comprises receiving an electronic message. In response to determining that the electronic message includes an express indication from a user that a classification applies or does not apply, the method comprises identifying message attributes of the electronic message that correspond to policy attributes of a machine learning policy and determining values of the policy attributes based on the identified message attributes. The method additionally comprises providing information to a machine learning trainer adapted to train the machine learning policy based on the information. The information comprises the values of the policy attributes and information indicating the classification that applies or does not apply to the electronic message, where such information is based on the express indication that the user included in the electronic message.

Abstract: A technique is described herein for processing a given query item in a latency-efficient and resource-efficient manner. The technique uses a first transformer-based encoder to transform the given query item into an encoded query item. In one case, the given query item is an expression that includes one or more query-expression linguistic tokens. The technique includes a second transformer-based encoder for transforming a given target item into an encoded target item. The given target item may likewise correspond to an expression that includes one or more target-expression linguistic tokens. A similarity-assessing mechanism then assesses the semantic similarity between the given query item and the given target item based on the encoded query item and the encoded target item. Each transformer-based encoder uses one or more self-attention mechanisms. The second transformer-based encoder can optionally perform its work in an offline manner, prior to receipt of the given query item.

Abstract: Systems and methods are disclosed to implement a machine learned system to determine the comparative relationship between item package quantity (IPQ) information indicated in two item descriptions. In embodiments, the system employs a neural network that includes a token encoding layer, an attribute summarizing layer, and a comparison layer. The token encoding layer accepts an item description as a token sequence and encodes the tokens with token attributes that are relevant to IPQ extraction. The attribute summarizing layer uses a convolutional neural network to generate a set of fixed-size feature vectors for each encoded token sequence. All feature vectors for both item descriptions are then provided to the comparison layer to generate the IPQ comparison result. Advantageously, the disclosed neural network model can be trained to make accurate predictions about the IPQ relationship of the two item descriptions using a small set of token-level attributes as input signals.

Abstract: Systems and methods for automated document graphing are disclosed. In one embodiment, in an information processing apparatus comprising at least one computer processor, a method for automated document graphing may include: (1) receiving, from a document repository, a plurality of source documents; (2) extracting text from each of the plurality of source documents; (3) cleaning the extracted text by removing unnecessary characters from the extracted text; (4) rewriting multi-word proper nouns in the extracted text; (5) converting a plurality of words in the extracted text to lemma form; (6) rewriting compound terms in the extracted text; (7) removing stop words from the extracted text; (8) representing each of the remaining words in the extracted text as a vector; and (9) storing the vectors in a library.

Abstract: An embodiment may involve transmitting, to a first client device, a representation of a first graphical user interface. The first graphical user interface may define fillable web-based forms. The embodiment may involve receiving, from the first client device, a first submission of the fillable web-based forms. The embodiment may involve transmitting, to a second client device, a representation of a second graphical user interface. The second graphical user interface may allow the second client device to fill out the fillable web-based forms. The embodiment may further involve receiving, from the second client device, a second submission of the fillable web-based forms. The embodiment may further involve determining numerical scores associated with each of the fillable web-based forms. The embodiment may also involve transmitting a representation of a third graphical user interface. The third graphical user interface may show the fillable web-based forms and their respective numerical scores.

Abstract: The disclosure provides a system that can easily calculate a similarity rate of a target document when comparing the target document. An array set of a designated type of words (e.g., nouns) is respectively extracted from a test document and a reference document as an arrayed test document and an arrayed reference document. A word included in a common word set of the arrayed test document and the arrayed reference document is defined as true as a proposition, and other words are defined as false as propositions. Further, when a ratio of words defined as true as propositions in a word array of a first designated length including a word among words defined as false as propositions is greater than or equal to a first designated value, the word is redefined as a wildcard and true as a proposition.

Abstract: Automated detection of personal information in free text, which includes: automatically applying a named-entity recognition (NER) algorithm to a digital text document, to detect named entities appearing in the digital text document, wherein the named entities are selected from the group consisting of: at least one person-type entity, and at least one non-person-type entity; automatically detecting at least one relation between the named entities, by applying a parts-of-speech (POS) tagging algorithm and a dependency parsing algorithm to sentences of the digital text document which contain the detected named entities; automatically estimating whether the at least one relation between the named entities is indicative of personal information; and automatically issuing a notification of a result of the estimation.

Abstract: A system, computer program product, and method are provided for employing a graph neural network (GNN) to construct a taxonomy. The GNN is subject to a training cycle and an inference cycle. The training cycle encodes cross-domain terms pairs from a set of noisy cross domain pairs extracted from a corpora, and outputs a preliminary taxonomy. The inference cycle identifies candidate term pairs and selectively subjects the candidate term pairs to selective filtering to produce a system predicted taxonomy from the preliminary taxonomy.

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: An information processing apparatus includes circuitry configured to acquire first form definition information defining a positional relationship between one or more items and a respective value of the one or more items stored in a memory, recognize and extract a specific item set with a specific character string and a specific value of the specific item from data of a form image based on the first form definition information as a recognition result, and display, on a display, the recognition result and an input reception section used for receiving an input of second form definition information.

Abstract: A system is provided for referral object processing for textual annotations. The system comprises a memory storing machine executable code and one or more processors coupled to the memory and configurable to execute the machine executable code to cause the one or more processors to parse a document to identify a reference identifier to an external object, the external object associated with information not contained in the document, retrieve the external object using the reference identifier, extract the information associated with the external object based on at least one data pattern detected in the external object, convert the extracted information into textual annotations associated with the reference identifier in the document, and enter the textual annotations to a corpus of content for the document so that the extracted information is associated with the reference in the document for the system.