Abstract: In methods and systems for providing information to a user relating to a point-of-interest (POI), a query is received via a communication network. A processor receives information relating to at least one POI based on the received query. The retrieved information comprises a set of retrieved POI tips relating to the POI. Each of the set of retrieved POI tips is previously extracted from POI free-text reviews and respectively associated in the data storage with one or more semantic categories based on a predefined tip ontology. The processor generates a user interface interactively displaying the retrieved POI tips and the semantic categories associated with each of the POI tips. The displayed POI tips are sorted by their associated displayed semantic categories. The generated user interface is transmitted to a computing device for display.

Abstract: A computer-implemented method for training a neural end-to-end aspect based sentiment analysis (ABSA) system includes: inputting a batch of samples of a dataset into the neural end-to-end ABSA system, where the neural end-to-end ABSA system includes: a contextual language encoder configured to embed tokens with context; a first self-attention network configured to, based on an output of the contextual language encoder, detect an aspect term and provide a first output corresponding to the aspect term; and a second self-attention network configured to, based on the output of the contextual language encoder, detect the aspect term and provide a second output corresponding to the aspect term; and based on the inputted batch of samples and a consistency loss function, selectively adjusting weights of the neural end-to-end ABSA system based on consistent aspect term detection by the first self-attention network and the second self-attention network.

Abstract: An annotation assistant for semi-automatic creation of annotated machine learning training data comprises a graphical annotation interface provider that provides a graphical annotation interface for displaying a sequence of tokens to be annotated and allowing a span selection by a user. An automatic span tagger comprises an artificial neural network configured to assign class probabilities to the tokens of the sequence of tokens and a processor-based path-scoring algorithm for computing scores for semantic attribute paths of the span selection. The graphical annotation interface is further configured for displaying the scored semantic attribute paths, and for receiving a selection among the scored semantic attribute paths from the user.

Abstract: In methods and systems for providing information to a user relating to a point-of-interest (POI), a query is received via a communication network. A processor receives information relating to at least one POI based on the received query. The retrieved information comprises a set of retrieved POI tips relating to the POI. Each of the set of retrieved POI tips is previously extracted from POI free-text reviews and respectively associated in the data storage with one or more semantic categories based on a predefined tip ontology. The processor generates a user interface interactively displaying the retrieved POI tips and the semantic categories associated with each of the POI tips. The displayed POI tips are sorted by their associated displayed semantic categories. The generated user interface is transmitted to a computing device for display.

Abstract: A single use packing, dispensing, and rinsing technique, where a strainer element is a permanent part of the packaging, placed opposite of the primary opening, to allow a user to drain liquid contents from a container (packing fluid or user-introduced) while retaining the solid contents.

Abstract: A method for categorizing an issue includes, for each of a plurality of categories of issue, providing at least one discourse pattern for identify text sequences that meet the discourse pattern. At least one of the discourse patterns specifies that an instance of a domain term in a domain term vocabulary be present in the text sequence for the pattern to be met. An issue is received which includes a text sequence. The text sequence is categorized based on which, if any, of the discourse patterns are met by the text sequence of the received issue. Information based on the categorization of the text sequence is output.

Abstract: A method for categorizing an issue includes, for each of a plurality of categories of issue, providing at least one discourse pattern for identify text sequences that meet the discourse pattern. At least one of the discourse patterns specifies that an instance of a domain term in a domain term vocabulary be present in the text sequence for the pattern to be met. An issue is received which includes a text sequence. The text sequence is categorized based on which, if any, of the discourse patterns are met by the text sequence of the received issue. Information based on the categorization of the text sequence is output.

Abstract: Systems and methods for aspect-based opinion mining including identifying the polarity (e.g., positive, negative, etc.) of different features of a product or a service as expressed in a text. This general task can be divided into four sub-tasks: identifying the aspect terms, classifying them into one of a set of predefined aspect categories, and identifying the polarity of the aspects terms and the aspect categories. A combination of systems (e.g., rule-based and machine learning based) can be employed to implement aspect category and aspect term polarity mutual annotation for aspect-based sentiment analysis.

Abstract: A method for aspect categorization includes receiving an input text sequence and identifying aspect terms and sentiment phrases in the input text sequence, where present. For an identified aspect term, identifying sentiment dependencies in which the aspect term is in a syntactic dependency with one of the identified sentiment phrases, and identifying pseudo-dependencies from a dependency graph of the input text sequence. The dependency graph includes a sequence of nodes. In a pseudo-dependency, a node representing the aspect term precedes or follows a node representing a semantic anchor in the dependency graph without an intervening other aspect term. Features for the aspect term are extracted from at least one of identified sentiment dependencies and identified pseudo-dependencies. With a classifier trained to output at least one of category labels and polarity labels for aspect terms, classifying the identified aspect term based on the extracted features.

Abstract: Systems and methods for acquiring information associated with a user by using NLP techniques are disclosed. One or more phrases are classified in one or more categories at least partly on the basis of a period for which a product has been used by the user, the user's experience with the product, preferences of the user, or needs of the user by applying one or more natural language processing (NLP) techniques. The one or more phrases are extractable from an electronic publication at least partly on the basis of on a predefined set of verbs, a predefined set of domain-specific terms, and terms indicative of temporal information. One or more terms from the classified phrases are extracted, in which the one or more terms are indicative of the information about the user.

Abstract: The present invention provides a system providing a suite of functions for automatically analyzing MRI images of brains to quantitatively assess brain development in children and adolescents. The system compares MRI images of a subject's brain to a database of normal brains, identifies regions showing abnormal growth, structure, and/or morphology, and notifies the health care provider of such abnormalities. The health care provider is notified by way of a graphical image depicted on a display highlighting the abnormal area(s) of the brain.

Abstract: Systems and methods for aspect-based opinion mining including identifying the polarity (e.g., positive, negative, etc.) of different features of a product or a service as expressed in a text. This general task can be divided into four sub-tasks: identifying the aspect terms, classifying them into one of a set of predefined aspect categories, and identifying the polarity of the aspects terms and the aspect categories. A combination of systems (e.g., rule-based and machine learning based) can be employed to implement aspect category and aspect term polarity mutual annotation for aspect-based sentiment analysis.

Abstract: A computer implemented method of forming carpools. Lists of participants in a rideshare environment are maintained. The participants are members of a private group and have privileges based on membership. A location of a participant is automatically determined based on a location detection method. A driver from the list of participants is automatically identified based on a current location of the driver. The driver proposes a trip comprising an approximate start time, approximate start location, end location, and number of available seats. Requests for transportation are received from passengers who are participants on the list of participants. For each available seat, the requests for transportation are automatically matched with the trip based on the approximate start time, the approximate start location, or the end location. Only certain passengers are matched with certain drivers. The matching identifies proposed riders.

Abstract: A method for processing micro-blogs includes, for each of a set of hashtags extracted from a collection of micro-blogs, decomposing the hashtag to generate a sequence of words and natural language processing the decomposed hashtag with rules configured for identifying syntactic dependencies and targets, such as proper names, in the dependencies. Opinion detection rules are applied to the detected dependencies which are configured for extracting opinion information from decomposed hashtags, such as a polarity based on presence of a polar term in a dependency. At least some of the hashtags in the set of hashtags are stored in a hashtag lexicon, the stored hashtags being associated with the extracted opinion information. A computer processor may perform the decomposing, natural language processing, applying opinion detection rules, and storing of the hashtags.

Abstract: A system and method for natural language processing of queries are provided. A lexicon includes text elements that are recognized as being a proper noun when capitalized. A natural language query includes a sequence of text elements including words. The query is processed. The processing includes a preprocessing step, in which part of speech features are assigned to the text elements in the query. This includes identifying, from a lexicon, a text element in the query which starts with a lowercase letter and assigning recapitalization information to the text element in the query, based on the lexicon. This information includes a part of speech feature of the capitalized form of the text element. Then parts of speech for the text elements in the query are disambiguated, which includes applying rules for recapitalizing text elements based on the recapitalization information.

Abstract: A system and method for extraction of suggestions for improvement form a corpus of documents, such as customer reviews, are disclosed. A structured terminology provided or a topic includes a set of semantic classes, each including a set of terms. A thesaurus of terms relating to suggestions of improvement is provided. Text elements of text strings in the documents which are instances of terms in the structured terminology are labeled with the corresponding semantic class and text elements which are instances of terms in the thesaurus are also labeled. A set of patterns is applied to the labeled text strings to identify suggestions of improvement expressions. The patterns define syntactic relations between text elements, some of which are required to be instances of one of the terms in a particular semantic class or thesaurus. A set of suggestions for improvements is output based on the identified suggestions of improvement expressions.

Abstract: Systems and methods for acquiring information associated with a user by using NLP techniques are disclosed. One or more phrases are classified in one or more categories at least partly on the basis of a period for which a product has been used by the user, the user's experience with the product, preferences of the user, or needs of the user by applying one or more natural language processing (NLP) techniques. The one or more phrases are extractable from an electronic publication at least partly on the basis of on a predefined set of verbs, a predefined set of domain-specific terms, and terms indicative of temporal information. One or more terms from the classified phrases are extracted, in which the one or more terms are indicative of the information about the user.

Abstract: A method for extracting opinion-related patterns includes receiving a corpus of reviews, the reviews each including an explicit rating of a topic. The reviews are partitioned among a predefined plurality of classes, based on the ranking. Syntactic relations are identified in each review. The syntactic relations may each include an adjective and a noun. A set of patterns is generated, each of the patterns having at least one of the identified syntactic relations as an instance and the patterns clustered into a set of clusters based on a set of features. At least one of the features is based on occurrences, in the predefined classes, of the instances of the patterns. A polarity is assigned to ones of the clusters and propagated to patterns in the respective clusters. The polarity-labeled patterns can each be instantiated as a contextual rule for opinion mining.

Abstract: An authoring assistant includes a parser which automatically identifies opinion expressions in input text. The text may include an author's review of an item, such as a product or service. A computer-implemented opinion review component generates an analysis of the text, which is based on the identified opinion expressions. The opinion review component computes an effective opinion of the text as a function of a measure of polarity associated with the identified opinion expressions. A representation generator generates a representation of the analysis for display on an associated user interface. The representation of the analysis includes a representation of the effective opinion. In the case of a review, the authoring assistant may allow the author to modify the review to reduce incoherence with a rating of the item.

Abstract: A system, method, and computer program product for generating a polar vocabulary are provided. The method includes extracting textual content from each review in a corpus of reviews. Each of the reviews includes an author's rating, e.g., of a specific product or service to which the textual content relates. A set of frequent nouns is identified from the textual content of the reviews. Adjectival terms are extracted from the textual content of the reviews. Each adjectival term is associated in the textual content with one of the frequent nouns. A polar vocabulary including at least some of the extracted adjectival terms is generated. A polarity measure is associated with each adjectival term in the vocabulary which is based on the ratings of those reviews from which the adjectival term was extracted.