Abstract: A digital advertising system includes at least one processor configured to execute a plurality of functional modules including an analytics module to receive and analyze client attributes associated with a website visitor and a requested website to define an analytics event. The analytics module ingests and enriches data within the analytics event and provides it to a machine learning module that generates prediction models for potential bids. A management platform receives the bidding prediction and generates candidate configs. An optimization module receives the candidate configs and applies weights and additional features to select a config and generate an optimized script for the selected config. A deployment module receives the optimized script and delivers the script to the website visitor.

Abstract: Disclosed are systems, methods, and devices for presenting customer insights in association with an electronic customer relationship management tool. A graphical user interface (GUI) is presented to a user. The GUI has a first region having GUI elements of the customer relationship management tool, and a second region having GUI elements for presenting at least one customer insight, the second region displayed when the first region is displayed and proximate to the first region. Upon receiving an identifier identifying a particular customer, at least one machine-learning derived insight relevant to the identified customer is displaying to the user in the second region when receiving user input signals via the GUI elements of the first region.

Abstract: Described herein is a technique to facilitate filtering during candidate retrieval stage performed by an information retrieval system that utilizes embedding models. An aNN indexing structure is created for each end-user, and in some instances, each activity type. This allows a single request for candidate content items to invoke a single process to obtain content items that satisfy the filtering criteria (e.g., in this case, the in-network requirement) from the separate per-end-user indexes.

Abstract: Techniques are disclosed relating to performing a join operation with bitmap indexes of virtual data sources (VDSs). A distributed compute cluster having a set of compute nodes may maintain a plurality of VDSs based on a set of corresponding origins. A given VDS of the plurality of VDSs may include a bitmap index representative of a portion of data stored at the set of origins. The distributed compute cluster may receive a request for data stored across at least first and second bitmap indexes of the plurality of VDSs. The distributed compute cluster may perform a join operation to generate a join result having data from the first and second bitmap indexes. The distributed compute cluster may return a response that includes the join result.

Abstract: The present invention relates to a system and a method for updating data models. Input data received from a data source and/or prediction data obtained from a data model is reduced based on baseline reference data to obtain a plurality of representative points. The plurality of representative points are clustered to generate a plurality of clusters. An outlier cluster is detected from the plurality of clusters based on a maximum distance of the plurality of clusters from a highest density cluster and/or comparison of quantity and values of the plurality of representative points with predefined rules. Data drift is identified based on changes in densities of the plurality of clusters. The data model is updated using information corresponding to the outlier cluster and the data drift.

Abstract: An exemplary embodiment provides an autoencoder which is explainable. An exemplary autoencoder may explain the degree to which each feature of the input attributed to the output of the system, which may be a compressed data representation. An exemplary embodiment may be used for classification, such as anomaly detection, as well as other scenarios where an autoencoder is input to another machine learning system or when an autoencoder is a component in an end-to-end deep learning architecture. An exemplary embodiment provides an explainable generative adversarial network that adds explainable generation, simulation and discrimination capabilities. The underlying architecture of an exemplary embodiment may be based on an explainable or interpretable neural network, allowing the underlying architecture to be a fully explainable white-box machine learning system.

Abstract: Embodiments of the present disclosure provide to techniques for automatically grouping software applications based on their technical patterns/characteristics (i.e., technical facets) via machine learning (ML) algorithms. For instance, a first set of software applications that exhibit a high prevalence of one or more first technical facets may be grouped into a first category, a second set of software applications that exhibit a high prevalence of one or more second technical facets may be grouped into a second category, and so on. Once grouped into categories, the software applications in a given category may be assessed, analyzed, and/or processed together for various purposes.

Abstract: Unsorted sparse dictionary encodings are transformed into unsorted-dense or sorted-dense dictionary encodings. Sparse domain codes have large gaps between codes that are adjacent in order. Unlike spare codes, dense codes have smaller gaps between adjacent codes; consecutive codes are dense codes that have no gaps between adjacent codes. The techniques described herein are relational approaches that may be used to generate sparse composite codes and sorted codes.

Abstract: A computer-implemented system and method for planning recurring events is provided. Event objects for events are stored in a database. A trigger notifying the beginning of an event is received and an event object representing the event is generated in response to the trigger. An event class is associated with a set of parameters and is assigned to the event object. A set of activity data is created for the event object and each activity data includes structured and unstructured data describing an event activity occurred during the event. At least one event object is retrieved from the database as a model and the parameter values of the model event object are displayed. At least one of the parameter values of the model event object is modified and the modification is reflected against other parameter values of the model event object that are dependent on the modified parameter value.

Abstract: Techniques for obtaining information about data entity instances managed by a data processing system using at least one data store. The techniques include obtaining a query comprising a first portion comprising information for identifying instances of a first data entity stored in at least one data store; and a second portion indicating at least one attribute of the first data entity; generating, from the query, a plurality of executable queries including a first set of one or more executable queries and a second set of one or more executable queries, the generating comprising: generating, using the first portion, the first set of executable queries for identifying instances of the first data entity, and generating, using the second portion, the second set of executable queries for obtaining attribute values for instances of the first data entity; and executing the plurality of executable queries to obtain results for the query.

Abstract: The invention relates to generating compressed channel state information and restoring the channel state information from the compressed channel state information. A computation device for compressing channel state information, CSI, representing a channel transfer function H having a spatial dimension and a frequency dimension comprises a transforming unit configured to perform a spatial transformation and a frequency-to-time transformation subsequently and in any order on the channel transfer function H to obtain a transformed channel transfer function HT, and a compressing unit configured to select values of the transformed channel transfer function HT and to generate compressed channel state information, CCSI, based on the selected values.

Abstract: A system includes a communications interface configured to receive a plurality of data series captured by a plurality of sensors. A first database includes at least a first data series of the plurality of data series. A second database includes metadata related to the first data series. One or more processors are configured to receive an instruction including an indication of a computation to perform and metadata filter criteria, query the second database to determine at least a portion of the first data series that satisfies the metadata filter criteria by reference to at least the metadata related to the first data series, access, from the first database and based on results of the query of the second database, the portion of the first data series, and perform the computation on the portion of first data series accessed from the first database.

Abstract: A computer-implemented method includes representing a plurality of database tables as respective vectors in a multi-dimensional vector space, receiving an indication that a first database table represented by a first vector and a second database table represented by a second vector are related to each other, moving positions of the respective vectors representing the plurality of database tables in the multi-dimensional vector space in response to the indication, and grouping the plurality of database tables into one or more table clusters based on positions of the respective vectors representing the plurality of database tables in the multi-dimensional vector space.

Abstract: Systems and techniques are provided for processing streaming data. For example, a process can include obtaining, by an edge device, a plurality of data streams corresponding to objects, activities, or events registered in an edge environment associated with the edge device. One or more machine learning networks implemented on the edge device can generate a plurality of features and/or embeddings corresponding to each respective data stream of the plurality of data streams. The edge device can determine a subset of salient content from the plurality of data streams, based on analyzing the plurality of features and/or embeddings generated for each respective data stream. The edge device can generate index information corresponding to the determined subset of salient content. The subset of salient content and the generated index information can be stored locally at the edge device for search and retrieval based on local queries received at the edge device.

Abstract: Aspects include processors configured to (or include program code that causes a processor to) provide for data classifier devices that extract from structured text business data inputs, via natural language understanding processing, training set data elements (for example, training keywords, training concepts, training entities, and/or training taxonomy classifications, etc.). The aspects identify associations within the structured training business data of each of a plurality of business class categories with respective ones of the extracted training set data elements; and build a logical relationship data classification training knowledge base ontology that connects ones of the business classes to respective associated ones of the extracted training data elements as questions, into a plurality of knowledge base ontology question-business class associations.

Abstract: A storage node of a database replica group may distribute different portions of data in local storage and external storage, where local storage and external storage are organized using different types of index structures. Responsive to receiving an access request for a database, a storage node may determine that an item of the database to be accessed by the request does not reside within a first portion of the database stored locally at the storage node. Responsive to this determination, the storage node may obtain from an external storage service a second portion of the database, the second portion including a plurality of items including the item, and the second portion organized according to a structure different from the first portion. The storage node may then store the plurality of obtained items in the first portion and process the request using the first portion of the database.

Abstract: Data classification extracts from structured text business data inputs, via natural language understanding processing, training set data elements (training keywords, training concepts, training entities, and/or training taxonomy classifications). Embodiments identify associations within the structured training business data of business class categories with respective ones of extracted training set data elements, and build a logical relationship data classification training knowledge base ontology that connects business classes to respective associated ones of extracted training data elements as questions into knowledge base ontology question-business class associations.

Abstract: Embodiments are directed to techniques for interacting with a hierarchical video segmentation by performing a metadata search. Generally, various types of metadata can be extracted from a video, such as a transcript of audio, keywords from the transcript, content or action tags visually extracted from video frames, and log event tags extracted from an associated temporal log. The extracted metadata is segmented into metadata segments and associated with corresponding video segments defined by a hierarchical video segmentation. As such, a metadata search can be performed to identify matching metadata segments and corresponding matching video segments defined by a particular level of the hierarchical segmentation. Matching metadata segments are emphasized in a composite list of the extracted metadata, and matching video segments are emphasized on the video timeline. Navigating to a different level of the hierarchy transforms the search results into corresponding coarser or finer segments defined by the level.

Abstract: Systems and methods for generating tables are provided. The systems and methods perform operations comprising accessing a text document comprising a plurality of strings; processing the text document by a machine learning model to generate a table comprising a plurality of entries that organizes the plurality of strings into rows and columns over a plurality of iterations; and at each of the plurality of iterations, estimating by the machine learning model a first value of a first entry of the plurality of entries based on a second value of a second entry of the plurality of entries that has been determined in a prior iteration.

Abstract: Provided is a method including obtaining a set of ontologies mapping n-grams onto concepts to which the n-grams refer in different respective domains of knowledge. The method includes receiving an update associating a first n-gram with a first concept and receiving information by which the update is associated with a given domain of knowledge. The method includes selecting a subset of ontologies by determining that the update in the given domain of knowledge is applicable to respective domains of knowledge of the subset of ontologies and that the first concept has a specified type of relationship to a subset of concepts to which other n-grams are mapped in the subset of ontologies. The method also includes storing, in response to the determination, associations between the first n-gram and the subset of concepts in at least some of the subset of ontologies in memory of the computer system.

Abstract: An apparatus includes a camera and a processing circuit. The camera may be configured to capture images of an environment around a vehicle. The processing circuit may be configured to (i) perform automated number-plate recognition using the images, (ii) store a history of detected license plates, and (iii) search the history of detected license plates in response to receiving a request from a communication device of a vehicle user for information matching the request.

Abstract: A data storage device includes a memory device and a controller coupled to the memory device. The controller is configured to program key value (KV) pair data to the memory device, where the KV pair data includes a key and a value, analyze the key, and generate metadata based on the analyzing. The controller is further configured to generate a metadata index for a plurality of KV pair data, where the metadata index value corresponds to a similarity or a difference between a first key and a second key, and cluster generated metadata based on the metadata index. The controller is further configured to receive a read command for the KV pair data, analyze the generated metadata of the KV pair data, generate a predicted next key, and use read look ahead (RLA) to read a predicted next KV pair data based on the predicted next key.

Abstract: Examples of the present disclosure describe systems and methods for aliased data insertions/retrieval for key-value stores. In aspects, a data set comprising a primary key, one or more secondary keys (“aliases”), and data values may be received by a data storage system. The system may allocate an internal identifier to the primary key and store the internal identifier and the primary key in a first table. Each of the secondary keys may be used to create a key-value pair comprising the secondary key and the internal identifier. The key-value pair(s) may be stored in the first table with the corresponding primary key. The internal identifier and the data values may be stored in a second table. Subsequently, the primary or secondary key may be used to interrogate the first table for the internal identifier. The internal identifier may then be used to interrogate the second table for the data values.

Abstract: Embodiments of the present disclosure provide techniques for efficiently and accurately performing propagation of search-head specific configuration customizations across multiple individual configuration files of search heads of a cluster for a consistent user experience. The cluster of search heads may be synchronized such that the search heads operate to receive the configuration or knowledge object customizations from one or more clients from a central or lead search head. To reduce the amount of data that is transferred during propagation, the list of configuration or knowledge object customizations maintained in each search head is filtered from the list of the lead search head until a divergence point is determined. Once determined and communicated to the lead search head, the lead search head sends the configuration and knowledge object customization data that is absent from the internal list of the member search head.

Abstract: Embodiments are directed to techniques for interacting with a hierarchical video segmentation by performing a metadata search. Generally, various types of metadata can be extracted from a video, such as a transcript of audio, keywords from the transcript, content or action tags visually extracted from video frames, and log event tags extracted from an associated temporal log. The extracted metadata is segmented into metadata segments and associated with corresponding video segments defined by a hierarchical video segmentation. As such, a metadata search can be performed to identify matching metadata segments and corresponding matching video segments defined by a particular level of the hierarchical segmentation. Matching metadata segments are emphasized in a composite list of the extracted metadata, and matching video segments are emphasized on the video timeline. Navigating to a different level of the hierarchy transforms the search results into corresponding coarser or finer segments defined by the level.

Abstract: Example implementations include determining, based on participant objects input into a machine learning model, to transmit a query to a third-party application based on a machine learning model trained with historical data associated with opportunities provided by third-party applications, transmitting to a third-party application, the query constructed based on a template compatible with an application programming interface (“API”) of the third-party application, receiving a response from the third-party application including an event and a profile for a participant of a service provided by the third-party application, the profile linked with a participant object and generated in response to importing information associated with the profile from a third-party administrator device, the event indicative of an opportunity to reduce resource utilization, determining that the participant object satisfies a parameter of the event, and providing to a computing device of the participant object responsive to satisfac

Abstract: Methods, apparatuses, computer-readable mediums for storing software, and systems for dynamic geographical spectrum sharing (DGSS) by Earth exploration satellite services (EESS) are described herein. Using DGSS mechanisms described herein, electromagnetic spectrum may be shared by sensors onboard Earth exploration satellites and wireless networks, such as 5G networks. The DGSS mechanisms may include mechanisms for determining an instantaneous field of view (IFOV) and mechanisms for modifying transmission characteristics while network antennas and power radiated by such antennas are within a window encompassing the IFOV. For example, when the IFOV of a satellite sensor for measuring atmospheric water includes a 5G antenna, the power of the 5G antenna may be reduced, the 5G antenna may be prevented from utilizing a segment of the electromagnetic spectrum, etc.

Abstract: The technology disclosed describes systems and methods for generating feature vectors from resource description framework (RDF) graphs. Machine learning tasks frequently operate on vectors of features. Available systems for parsing multiple documents often generate RDF graphs. Once a set of interesting features to be considered has been established, the disclosed technology describes systems and methods for generating feature vectors from the RDF graphs for the documents. In one example setting, a machine learning system can use generated feature vectors to determine how interesting a news article might be, or to learn information-of-interest about a specific subject reported in multiple articles. In another example setting, viable interview candidates for a particular job opening can be identified using feature vectors generated from a resume database, using the disclosed systems and methods for generating feature vectors from RDF graphs.

Abstract: First and second trees having entities identified by hexadecimal values are generated. First files are allocated across the first tree based on hashes of the first files and hexadecimal values of the first tree entities. First index values are calculated for first tree entities using hashes of the first files that have been allocated to entities branching into a lower level of the first tree. Second files are allocated across the second tree based on hashes of the second files and hexadecimal values of the second tree entities. Second index values are calculated for the second tree entities using hashes of the second files that have been allocated to entities branching into a lower level of the second tree. A determination is made of a number of entities between the first and second trees having matching index values to measure similarity between the first and second trees.

Abstract: Systems and methods to copy a plurality of source data records of a source client to a target client include deletion of a first set of target data records of a plurality of target data records associated with the target client, each of the first set associated with a key which is not identical to any key of a plurality of source data records, insertion of a second set of source data records into the plurality of target data records, each of the second set of source data records associated with a key which is not identical to any key of the plurality of target data records, and update of a third set of target data records associated with a key which matches a key of one of the fourth set of source data records and which is different from one of the fourth set of source data records.

Abstract: A data-driven nonuniform subsampling approach for computation-free on-sensor data dimensionality is provided, referred to herein as selective sensing. Designing an on-sensor data dimensionality reduction scheme for efficient signal sensing has long been a challenging task. Compressive sensing is a generic solution for sensing signals in a compressed format. Although compressive sensing can be directly implemented in the analog domain for specific types of signals, many application scenarios require implementation of data compression in the digital domain. However, the computational complexity involved in digital-domain compressive sensing limits its practical application, especially in resource-constrained sensor devices or high-data-rate sensor devices. Embodiments described herein provide a selective sensing framework that adopts a novel concept of data-driven nonuniform subsampling to reduce the dimensionality of acquired signals while retaining the information of interest in a computation-free fashion.

Abstract: Methods and systems for indexing data for a search tool are disclosed, wherein the method is performed using one or more processors. The methods and systems may comprise an operation of providing an indexing application programming interface (API) for implementation in relation to one or more data resources of a data processing platform requiring data of the data resource to be indexed for searching using a search tool of the data processing platform. The interface may be configured, when implemented in relation to a data resource, to send data indicative of one or more definitions of data to be crawled from said data resource to an indexing system of the data processing platform, and to generate an event queue indicative of one or more events associated with said defined data that have occurred in relation to the data resource.

Abstract: A computational instance may include, in database tables, representations of computing services provided by remote networks. One or more processors disposed in the computational instance may cause a computing-service-neutral cloud integration application to perform operations including: obtaining a specification related to a remote network, where the specification defines: (i) an integration point for the remote network, (ii) a pagination type associated with the integration point, and (iii) mappings between descriptions of the computing services provided by the remote network and fields of the database tables.

Abstract: The data storage system according to certain aspects can implement table level database restore. Table level database restore may refer to restoring a database table and its related data without restoring the entire database. The data storage system may use table metadata index to implement table level restore. A table metadata index may be created for each table, e.g., during a backup of the database. The table metadata index for a table can include any type of information for restoring the table and its related data. Some examples of the type of information included in the table metadata index include the following: container for the table, table backup location, system data, table index, table relationships, etc. Table metadata index can make the restoring of tables fast and efficient by packaging information that can be used to restore a table and its related data in an easily accessible manner.

Abstract: A database query specifies a user-defined function (UDF) to apply to one or more tables in a distributed database. The one or more tables are identified in the distributed database. The one or more tables are associated with an initial set of data types native to the distributed database. The one or more tables are converted to database data comprising data types of the UDF. The UDF is executed on the database data to generate results data. The results data is converted to table results data. The table results data is associated with the initial set of data types. The table results data is stored in the distributed database.

Abstract: A method, system and computer program product are disclosed for determining a shortest path between two nodes of a graph, where the graph is represented in one or more tables of a relational database as a plurality of records identifying edges between pairs of connected nodes in the graph. A request specifies a source node (or set of source nodes), a target node (or set of target nodes) and a maximum path length L. Each path length l, from 1 to L, is iteratively tested by first generating a query comprising a sequence of join operations for that path length, and secondly decomposing the join operations into a sequence of one or more tree-structured queries comprising semi-join operations. Each tree-structured query when executed as a sequence of semi-join operations will return either an empty result set, indicating that no shortest path exists at that path length, or a non-empty result set which identifies all edges at step k of each shortest path of length l, where 1?k?l.

Abstract: A system is disclosed to build and store a data model and queries for a graph database. In various embodiments, data defining one or more aspects of a data model associated with a graph database is received. A set of data that represents the data model is stored as a graph that includes one or more nodes to represent each of the following: data model metadata, one or more node labels comprising the graph database, one or more relationship types of the graph database, and one or more property definitions each associated with a property of at least one of a node label and a relationship type of the graph database.

Abstract: A computer readable medium includes a data set with data stored in rows and N columns. Each of the rows is associated with one individual patient. Each of the N columns is associated with one type of data for patients. One or more processors is configured to: initialize missing values in M ones of the N columns with M values for the M ones of the N columns, respectively; generate M mathematical models for the M ones of the N columns having one or more missing values; for each of the rows having one or more missing values, update ones of the M values for the M ones of the N columns; and fill missing values in the M ones of the N columns with the M values, respectively.

Abstract: A system for extracting latent information from data includes obtaining or generating components of the data, where the data components include scores indicating how the component relates to the data. Memory is allocated for the components and the components are stored in the allocated memory. The components are then transformed into documents using a suitable transformation function, and the documents are analyzed using natural language processing, to extract latent information contained in the data.

Abstract: Embodiments described herein are directed to measuring and improving an index quality of a distributed data system. For example, various quality metrics are determined on a per partition basis of the distributed data system. Each of the quality metrics are indicative of a quality of a particular property of a partition. The quality metrics are aggregated to generate an overall index quality score, which provides a measure of the performance of the index. The index quality score is utilized to automatically detect an inefficiency of the index and automatically determine that certain index maintenance actions should be automatically performed to improve the performance of the index. Each quality metric may also be individually analyzed to determine which database property is affecting the performance of the index the most.

Abstract: Technology for the improved processing of search queries is provided. In one embodiment, methods may return semantically relevant search results for a search query. During a pre-computing offline processing, an inventory semantic index may be generated and may include inventory binary hashing signatures that are associated with inventory listings, such as goods or services for sell, and the index may be partitioned by categories and shards. When a search query is received, relevant categories are determined using a relevant category recognition service, and a search query binary hashing signature maybe generated for the search query. The relevant categories are searched to determine hamming distances between the inventory binary hashing signatures and the search query binary hashing signature, where the hamming distance indicates semantic relevance.

Abstract: A data enrichment system for enriching requests for advertising opportunities. The data enrichment system is configured to aggregate and index data to provide end user insights to marketers based upon information supplied by publishers in regards to advertising opportunities passed along in requests. The system is configured to take attributes passed along in a request associated with the advertising opportunity and provide enriched data based upon the attributes received in the request. The attributes can then identify corresponding enriched data that can be passed along to the marketers.

Abstract: A computer-implemented method, system and computer program product for dynamically providing a typing feedback indicator. Text entered in a body of a message that is to be sent to a recipient is detected. Prior to the user (author) sending the message to the recipient, the text of the message being composed by the user is analyzed to determine a sentiment and an emotion as well as to determine a topic of the content of the text. Based on such analyses, as well as possibly based on other criteria, a typing feedback indicator is generated to reflect an indication of the content of the message to be sent to the recipient. The typing feedback indicator may then be displayed on a computing device of the recipient while the user (author) is composing the message thereby providing the recipient context awareness of the message prior to receipt of such a message.

Abstract: A method, computer system, and a computer program product for project development in a collaborative platform is provided. The present invention may include identifying one or more features of an open source project. The present invention may include analyzing the one or more features of the open source project and assigning a sentiment to each of the one or more features. The present invention may include generating a requirement mapping for the open source project, wherein the requirement mapping is a series of the one or more features.

Abstract: The present invention relates to data processing system and method in supply chain application. The data processing system includes clustering of received supply chain data after normalization, tokenization and vectorization through graph-based analysis.

Abstract: An adaptive action recognizer for video that performs multiscale spatiotemporal decomposition of video to generate lower complexity video. The adaptive action recognizer has a number of processing pathways, one for each level of video complexity with each processing pathway having a different computational cost. The adaptive action recognizer applies a decision making scheme that encourages using low average computational costs while retaining high accuracy.

Abstract: The present disclosure is directed towards a system, method, and computer readable storage medium for searchable encryption. A plurality of search terms are extracted from at least a part of a data structure. A keyed-hash value for each search term is calculated and stored in a list. The value of a bit in a predetermined position within each keyed-hash value is examined. If the value of the bit is a first value for ? of the keyed-hash values and a second value for ? of the keyed-hash values, wherein ? is a number greater or equal to two and the first value is different to the second value, then the set of keyed-hash values is split into two lists. Each list is assigned a search token value.

Abstract: A method for setting parameter settings of an image signal processor (ISP) of a camera of a mobile device based on a user selection may include controlling a display of the mobile device to display a plurality of images, each of which is associated with corresponding parameter settings. The method may include receiving, via a user interface (UI) of the mobile device, the user selection in relation to an image of the plurality of images. The method may include determining selected parameter settings based on the user selection in relation to the image. The method may include setting the parameter settings of the ISP, based on the selected parameter settings, to permit the ISP to process a raw image from an image sensor of the mobile device using the selected parameter settings.

Abstract: In an embodiment, a system can determine geocoded data from a database of geographic coordinates and metadata. The system correlates metadata, such as invoice data, to geolocation data, such as GPS or cellular data to determine geocoded data. The system further identifies one or more geographic coordinates for one or more location names, which may not have a corresponding metadata entry, by generating clusters of geographic coordinates. The clusters are then matched to one or location names using a matching algorithm. Accordingly, improved geocoded data may be determined.

Abstract: A method and system for providing replacement text segment suggestions for an unoriginal text segment in a document may include examining a portion of the document to determine if the portion includes a text segment containing unoriginal content. Upon determining that the portion includes the unoriginal text segment, the method may enable display of a notification that the text segment contains unoriginal content and receive a request, via a network, to provide the replacement text segment for the unoriginal text segment. Upon receiving the request, the method may identify the replacement text segment for the text unoriginal segment, based at least in part a guideline relating to the use of content that is included in a source. The replacement text segment may include a citation for the source.