Abstract: According to an embodiment of the present invention, a system dynamically produces a document with transformed terms associated with a geographic location, and comprises a computer system including at least one processor. The system analyzes a retrieved document to identify one or more terms with equivalent expressions in the same natural language. Each of the identified terms is transformed into an equivalent expression based on at least a geographic location associated with a user. The system produces a transformed document by replacing the identified one or more terms in the retrieved document with the equivalent expressions associated with the geographic location. Embodiments of the present invention further include a method and computer program product for dynamically producing a document with transformed terms for a geographic location in substantially the same manner described above.

Abstract: A method, a processing device, and a computer program product are provided. Via at least one processing device, each text file is selected from a collection of text files, wherein the collection of text files has an intensity with respect to negative sentiment toward a common issue. At least one profile algorithm is performed, each calculating a corresponding profile score for that text file. At least one corresponding profile score of the text files of the collection are combined to produce an aggregated profile score for each of at least one profile algorithm. The aggregated profile score of each of the at least one profile algorithm for the collection is stored. A signature for the collection of text files includes the aggregated profile score of each of the at least one profile algorithm for the collection.

Abstract: A computer-implemented method includes receiving a rule, wherein the rule includes at least one token, and receiving at least two dictionaries, wherein the at least two dictionaries include at least one general language dictionary and at least one domain-specific dictionary for a domain. The computer-implemented method further includes, for each of the at least one token, selecting at least one word at random from at least one of the at least two dictionaries and adding the at least one word to a test data line, such that the test data line includes a candidate statement conforming to the rule. The computer-implemented method further includes filtering the candidate statement based on a domain-specific model for the domain and including the candidate statement in training data provided to a machine learning model. A corresponding computer program product and computer system are also disclosed.

Abstract: A computer-implemented method includes receiving a rule, wherein the rule includes at least one token, and receiving at least two dictionaries, wherein the at least two dictionaries include at least one general language dictionary and at least one domain-specific dictionary for a domain. The computer-implemented method further includes, for each of the at least one token, selecting at least one word at random from at least one of the at least two dictionaries and adding the at least one word to a test data line, such that the test data line includes a candidate statement conforming to the rule. The computer-implemented method further includes filtering the candidate statement based on a domain-specific model for the domain and including the candidate statement in training data provided to a machine learning model. A corresponding computer program product and computer system are also disclosed.

Abstract: A computer system gleans data from patient records and clinical trial descriptions using NLP techniques. NLP annotation data is used to generate clinical trial feature vectors and patient feature vectors. Clinical trial feature vectors and patient feature vectors are compared to match appropriate patient candidates with clinical trial openings.

Abstract: A computer system gleans data from patient records and clinical trial descriptions using NLP techniques. NLP annotation data is used to generate clinical trial feature vectors and patient feature vectors. Clinical trial feature vectors and patient feature vectors are compared to match appropriate patient candidates with clinical trial openings.

Abstract: A method for providing annotation summaries for annotations is provided. The method may include receiving annotations associated with analyzed unstructured data. The method may further include sorting the received annotations. Additionally, the method may include receiving focal points on the analyzed unstructured data. The method may also include extracting the sorted annotations associated with the focal points. The method may further include normalizing terms and phrases associated with the extracted annotations. The method may also include determining topics based on the normalized terms and phrases associated with the extracted annotations. The method may further include grouping the extracted annotations based on the determined topics. The method may also include summarizing the grouped annotations to generate a summarized annotation. The method may further include replacing the extracted annotations with the summarized annotation.

Abstract: A method, a processing device, and a computer program product are provided. At least one processing device correlates textual medical information related to the subject with characteristics of an image of a medical condition of the subject to generate a subject signature. The at least one processing device compares the subject signature with multiple reference signatures to determine at least one reference signature corresponding to the subject signature. Each reference signature is associated with a corresponding medical condition and is generated by correlating textual medical information regarding the corresponding medical condition with characteristics of an image of the corresponding medical condition. The at least one processing device identifies the medical condition of the subject based on the medical conditions associated with the determined at least one reference signature. Information is provided regarding the identified medical condition of the subject.

Abstract: A method, a processing device, and a computer program product are provided. Via at least one processing device, each text file is selected from a collection of text files, wherein the collection of text files has an intensity with respect to negative sentiment toward a common issue. At least one profile algorithm is performed, each calculating a corresponding profile score for that text file. At least one corresponding profile score of the text files of the collection are combined to produce an aggregated profile score for each of at least one profile algorithm. The aggregated profile score of each of the at least one profile algorithm for the collection is stored. A signature for the collection of text files includes the aggregated profile score of each of the at least one profile algorithm for the collection.

Abstract: A method for providing annotation summaries for annotations is provided. The method may include receiving annotations associated with analyzed unstructured data. The method may further include sorting the received annotations. Additionally, the method may include receiving focal points on the analyzed unstructured data. The method may also include extracting the sorted annotations associated with the focal points. The method may further include normalizing terms and phrases associated with the extracted annotations. The method may also include determining topics based on the normalized terms and phrases associated with the extracted annotations. The method may further include grouping the extracted annotations based on the determined topics. The method may also include summarizing the grouped annotations to generate a summarized annotation. The method may further include replacing the extracted annotations with the summarized annotation.

Abstract: According to an embodiment of the present invention, a system dynamically produces a document with transformed terms associated with a geographic location, and comprises a computer system including at least one processor. The system analyzes a retrieved document to identify one or more terms with equivalent expressions in the same natural language. Each of the identified terms is transformed into an equivalent expression based on at least a geographic location associated with a user. The system produces a transformed document by replacing the identified one or more terms in the retrieved document with the equivalent expressions associated with the geographic location. Embodiments of the present invention further include a method and computer program product for dynamically producing a document with transformed terms for a geographic location in substantially the same manner described above.

Abstract: A method, a processing device, and a computer program product are provided. At least one processing device correlates textual medical information related to the subject with characteristics of an image of a medical condition of the subject to generate a subject signature. The at least one processing device compares the subject signature with multiple reference signatures to determine at least one reference signature corresponding to the subject signature. Each reference signature is associated with a corresponding medical condition and is generated by correlating textual medical information regarding the corresponding medical condition with characteristics of an image of the corresponding medical condition. The at least one processing device identifies the medical condition of the subject based on the medical conditions associated with the determined at least one reference signature. Information is provided regarding the identified medical condition of the subject.

Abstract: Techniques disclosed herein describe generating annotations for text content rendered on a web browser. The web browser is configured with a content analytics plug-in configured to receive content to render in the web browser. The content itself includes unstructured text. The content analytics plug-in evaluates the unstructured text using content analytics and natural language processing (NLP) techniques to characterize the meaning of one or more passages in the unstructured text. The content analytics plug-in then generates annotations based on the characterizations to display when the web browser renders the content.

Abstract: Techniques disclosed herein describe generating annotations for text content rendered on a web browser. The web browser is configured with a content analytics plug-in configured to receive content to render in the web browser. The content itself includes unstructured text. The content analytics plug-in evaluates the unstructured text using content analytics and natural language processing (NLP) techniques to characterize the meaning of one or more passages in the unstructured text. The content analytics plug-in then generates annotations based on the characterizations to display when the web browser renders the content.

Abstract: A method, a processing device, and a computer program product are provided. Unstructured text may be analyzed to identify medical condition information of multiple occurrences of a medical condition for at least one subject. Times and geographic locations corresponding to the multiple occurrences of the medical condition may be obtained. Environmental information that corresponds to the times and the geographic locations of the multiple medical condition occurrences, may be retrieved. Correlations between the medical condition information and the retrieved environmental information for the at least one subject may be determined. Environmental factors affecting the medical condition, based on the determined correlations, are identified.

Abstract: A lexical annotator that identifies a chunk of a communication and an associated sentiment is created. In real time, while monitoring a communication from a user, the lexical annotator is used to identify the sentiment for the chunk of the communication, and the sentiment for the chunk of the communication is provided.

Abstract: Generating structured queries from natural language text may include receiving, using a processor, a natural language text input directed to a database management system and, using the processor, performing natural language processing on the natural language text input using an Unstructured Information Management Architecture. The natural language processing may annotate the natural language text input according to a structure of the database management system. A database operation and query elements may be determined using a processor from the annotated natural language text input. A structured query may be created, using the processor, for the database management system that implements the database operation using the query elements.

Abstract: Embodiments presented herein provide techniques for generating a recipe using text analytics methods. A server application receives a search query for a specified dish (e.g., from a client computer). The application retrieves recipes relevant to the specified dish (e.g., by crawling websites on the Internet) and extracts text from each recipe. The application performs a variety of text analytics methods on the text to identify different ingredients and preparation methods in creating the dish. Additional analytics are performed to loosely predict a recipe that conforms to the search query as well as dietary restrictions of a user.

Abstract: Provided is a technique for providing an interactive dashboard based on real-time sentiment analysis for synchronous communication. In real time, while monitoring communications between a first user and a second user, a cumulative sentiment score is generated representing a sentiment of the first user during a period of time and an instantaneous sentiment score representing a sentiment of the first user at a current time. In real time, an interactive dashboard is displayed with a visual representation for the first user having a first indicator representing the cumulative sentiment score and a second indicator representing the instantaneous sentiment score.

Abstract: Techniques disclosed herein describe generating annotations for text content rendered on a web browser. The web browser is configured with a content analytics plug-in configured to receive content to render in the web browser. The content itself includes unstructured text. The content analytics plug-in evaluates the unstructured text using content analytics and natural language processing (NLP) techniques to characterize the meaning of one or more passages in the unstructured text. The content analytics plug-in then generates annotations based on the characterizations to display when the web browser renders the content.