Patent classifications
G06F16/90344
Search result output method, search result output method, and non-transitory computer-readable storage medium for storing program
A method for outputting a search result includes: executing a reception process that includes receiving a search query for target data; executing a candidate item identification process that includes referring to index information associating each of a plurality of items included in the target data with a position of a corresponding one of the items, and identifying a first storage area configured to store an item corresponding to a keyword included in the search query; and executing an addition process that includes when a description included in the corresponding one of the items includes a reference to a different item, referring to the index information, and adding information on a second storage area configured to store the different item to the reference to the different item.
User centric topics for topic suggestions
A data processing system implements receiving a request for user-centric topic recommendations from a computing device of a user in response to a user input in an application indicating that the user is attempting to assign a tag to a first content item in the application; obtaining a first set of user-centric topic recommendations from a first topic datastore based on a relevance ranking assigned to each of the topic recommendations; providing the first set of user-centric topic recommendations to the computing device; causing the computing device to display the first set of user-centric topic recommendations; receiving one or more second requests for user-centric topic recommendations; obtaining one or more second sets of user-centric topic recommendations from the first topic datastore based on the query string and the relevance ranking; and causing the computing device of the user to display the one or more second sets of user-centric topic recommendations.
STORING AND PROCESSING LONGITUDINAL DATA SETS
The invention relates to the processing of a data file containing one or more longitudinal data points relating to a subject. The data file is processed in a manner that reduces the risk of erroneously associating its constituent longitudinal data point(s) with an incorrect subject, or failing to associate the longitudinal data point(s) with previously gathered longitudinal data corresponding to the same subject. The invention has application in many fields including the performance of medical tests, particularly tests for biomarkers such as the ROCA test for CA125. Techniques for securely performing analysis of longitudinal data are also provided.
MACHINE REASONING AS A SERVICE
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for responding to a query. In some implementations, a computer obtains a query. The computer determines a meaning for each term in the query. The computer determines user data for the user that submitted the query. The computer identifies one or more ontologies based on the meanings for at least some of the terms. The computer identifies a knowledge graph based on the identified ontologies and the user data. The computer generates a response to the query by traversing a path of the identified knowledge graph to identify items in the knowledge graph based on the determined meaning for each of the terms. The computer generates path data that represents the path taken by the computer through the identified knowledge graph. The computer provides the generated response and the path data to the client device.
SYSTEMS AND METHODS FOR COMPRESSION-BASED SEARCH ENGINE
A system described herein may provide a technique for the compression of query terms and search data against which the query terms may be evaluated. The compression may be dynamic, in that a quantity of bits used to compress the search data and query terms may be based on a quantity of unique characters included in a given query term. The compression may further include reducing the volume of search data by compressing entire words, that do not include any of the unique characters of the query term, to one particular code.
String similarity determination
A system and a method for determining a similarity between a first string and a second string. A sequence of edit operations are performed on the first string in order to obtain the second string may be determined. The edit operation is of a first type or a second type. The first type operation comprises a character insertion operation or character removal operation. The second type operation comprises a character maintenance operation. The first type edit operation is associated with an operation score indicative of a cost for applying the edit operation. The first type edit operation is associated with a switching score indicative whether it is immediately followed by a second type edit operation. The switching scores and/or operation scores associated with the sequence of edit operations are combined in order to obtain a combined score that is indicative of the similarity level between the first and second strings.
DISPLAYING A DATABASE RECORD IN A CHAT PLATFORM
Provided herein are system, apparatus, device, method and/or computer program product embodiments, and/or combinations and sub-combinations thereof for displaying a database record in a chat platform. In a given embodiment, a server may detect a request to launch a search window, including an input field. The server may cause the display of the search window, including the input field, in response to detecting the request to launch the search window. The server may receive a string via the input field. The server may query a database for a database record matching the string. The server may receive a selection of the database record from the chat participant. The server may cause display of a subset of fields of the database record in the chat session.
AUTOMATIC DETECTION OF PERSONAL IDENTIFIABLE INFORMATION
Described herein are example implementations for the automatic detection and handling of personal identifiable information (PII) in electronic records. In some aspects, a system receives one or more computer readable logs of information for one or more computer services, with each log including a string of characters. The system performs one or more string search algorithm based operations on the entirety of the one or more strings of the one or more computer readable logs to identify a range of the one or more strings to be searched for PII that is less than the entirety of the one or more strings. The system also performs one or more regular expression algorithm based operations on the range of the one or more strings to identify one or more instances of PII. The system generates and outputs an indication of the one or more instances of the PII that are identified.
Service worker configured to serve multiple single page applications
Disclosed herein is a system configured to implement a service worker capable of serving multiple single page applications (SPAs) that are hosted in the same uniform resource locator (URL) space (e.g., a domain within which the SPAs are hosted). Accordingly, the defined scope of the service worker is no longer bound by only one SPA, but rather by a root directory of a web site that hosts multiple SPAs. Since the service worker described herein serves multiple SPAs, the service worker implements an approach to ensure that a correct application controller corresponding to the SPA that hosts a URL is invoked. To do this, the service worker is configured to leverage a router and a routing table to associate a URL included in a request from a browser with the correct application controller corresponding to the SPA that hosts the URL for which the request is sent.
MACHINE LEARNING (ML) MODEL FOR GENERATING SEARCH STRINGS
Embodiments illustrated herein disclose a method includes receiving a text input, wherein the text input corresponds to a search string. The method further includes converting the text input to a string vector. Additionally, method further includes retrieve, by the processor, one or more phrases in the text input. Further, the method includes predicting one or more technology classifications associated with the text input based on the string vector by utilizing a Machine Learning (ML) model. The method includes generating at least a first structured search string based on the one or more technology classifications and the one or more phrases.