269 results about "Content management system" patented technology

This disclosure describes systems that identify one or more models (e.g., large language models and / or virtual assistants) permitted to access content items stored for user accounts within a content management system. The disclosed systems can determine a model available to a user account within the content management system from among the one or more models. For example, the disclosed systems can determine one or more relationships between the user accounts within the content management system, large language models utilized by the user accounts, virtual assistants utilized by the user accounts, and content items accessed by the user accounts. The disclosed systems can determine the model for the user account according to the one or more relationships. The disclosed systems can provide a notification corresponding to the model via a user interface of a client device associated with the user account.

A multimodal content management system having a block-based data structure can include an artificial intelligence (AI)-based embeddings generator and indexer. After receiving an item update instruction that includes an object (e.g., a block content, a block property, or a block schema) identifier and an update payload, the system can transform the update payload—for example, by generating a chunk to capture at least a portion of the update payload. The chunk can correspond to a particular content modality included in the update payload. The system can generate and retrievably store a vector comprising a set of embeddings corresponding to the chunk, where the embeddings represent a vectorized portion of block content, block property, or block schema.

Systems and methods are provided herein for an advanced teleprompter with dynamic content management. The script management system (SMS) of this advanced teleprompter receives a transcript with consecutive sections of text for dynamic display at a client device and provides for dynamic display the consecutive sections of text at a first pace. After the SMS receives the transcript, the SMS ingests the prepared transcript and the given time frame for the speech, and then uses the transcript as an input for a large language model (LLM). Once the SMS detects speech from a speaker the SMS inputs the transcript and the text of the speech from the speaker into the LLM and modifies a section subsequent to the first section of text based on the output of the LLM that results from the inputs of the transcript and the text of the speech. The SMS then provides for dynamic display the modified section subsequent to the first section of text of the plurality of consecutive sections of text.

The present technology introduces a simple to use interface that integrates a mechanism to protect content items from use by one or more machine learning algorithms into interfaces of a content management system. In this way, the present technology can make it easy to protect content items where they are stored. The present technology protects against this use by providing options to obfuscate content in a way that can confound artificial intelligence systems during both training and use of the artificial intelligence systems. Additionally, the present technology can control access to content items shared using a link. The content management system can determine not to serve content items when requested by known artificial intelligence systems or services that train them. The present technology can also include automatic content protection rules that can cause the content management system to automatically protect content items when the content item is to be shared.

A multimodal content management system having a block-based data structure can include a query engine configured to perform automatic data discovery for natural language queries. The system can generate and render, at a computing device, a page comprising a graphical user interface (GUI) with a displayable item from a first block of a block-based data structure. The system can generate and bind, to the page, a schema definition comprising a first reference to the first block and a second reference to a set of blocks, wherein the first block is relationally linked to the set of blocks via the second reference. The system can use at least a portion of a natural language prompt, received at the GUI, to generate an input feature for a large language model, the input feature having a schema-question pair that includes at least a portion of the schema definition. The large language model can generate a query configured to operate on the block-based data structure.

This disclosure describes systems that identify one or more models (e.g., large language models and / or virtual assistants) permitted to access content items stored for user accounts within a content management system. The disclosed systems can determine a model available to a user account within the content management system from among the one or more models. For example, the disclosed systems can determine one or more relationships between the user accounts within the content management system, large language models utilized by the user accounts, virtual assistants utilized by the user accounts, and content items accessed by the user accounts. The disclosed systems can determine the model for the user account according to the one or more relationships. The disclosed systems can provide a notification corresponding to the model via a user interface of a client device associated with the user account.

The present disclosure relates to systems, non-transitory computer-readable media, and methods for integrating a content management system plugin with a large language model. In particular, in some embodiments, the disclosed systems integrate, into a computing environment of a large language model, a content management system plugin comprising computer code for an application programming interface (API) that facilitates operations by the large language model on content items stored in a content management system. Moreover, in some embodiments, the disclosed systems receive, from the large language model via the content management system plugin, a function call requesting performance of an API operation on a content item stored in the content management system. Furthermore, in some implementations, the disclosed systems execute the API operation on the content item stored in the content management system in response to the function call from the content management system plugin integrated within the large language model.

Disclosed embodiments provide techniques for computerized moderation, authorship recording, and distribution of social media content. Moderator-supplied tags are associated with content and supplied to a machine learning system as training data. Using blockchain, authorship is authenticated and can be converted from anonymous to non-anonymous. Collaboration among authors on content is supported with authorship lists that can contain a mix of anonymous and non-anonymous authors. Contribution limits are established to determine royalty payments for sale and rent of content.

An example for presenting educational content including converting a multimedia document into a text representation of the multimedia document, partitioning the text representation into multiple portions of text based on a text characteristic of the text representation; determining educational concepts associated with portions of text. Then, generating at least a first cluster and a second cluster where the first and second clusters include portions of text of the multiple portions of text, and each portion of respective text in the first cluster is associated with a first educational concept of the one or more educational concepts and each portion of respective text in the second cluster is associated with a second educational concept of the one or more educational concepts. From the clusters, generating a first educational content item based on the first cluster and a second educational content item based on the second cluster.

A system for evaluating responses generated by a language learning model (LLM) for a query from an end-user of a website of a website building system (WBS) includes an input processor, a content engine, a prompt generator, and a chat triad. The input processor receives the query. The content engine retrieves relevant content from a content management system (CMS) of the WBS. The prompt generator prompts the LLM to generate an answer according to the query and content. The chat triad evaluates relevance and accuracy of the generated answer by assigning relevance values to relationships between the query, content, and answer; determining a combined score; evaluating the score against criteria; and determining whether to present the answer to the end-user.

A multimodal content management system having a block-based data structure can include a question and answer (Q&A) assistant (e.g., a chatbot). The system can receive a natural language prompt and generate a result set. The result set can include blocks (e.g., blocks that include responsive content, including content in different modalities). The system can apply a set of authority signals to items in the result set to generate a ranked result set. The authority signals can be generated using aspects of the block-based data structure, such as block properties. The system can cause the Q&A assistant to return a set of hyperlinks to the ranked result set items. The hyperlinks can be operable to enable navigation to block content without closing the Q&A assistant.

The present disclosure is directed toward systems, methods, and non-transitory computer readable media for generating and searching a hybrid search index. In some embodiments, the disclosed systems generate a hybrid search index that comprises one or more content items stored at a content management system or at external network locations linked to the content management system via software connectors along with world state data associated with the one or more content items. The disclosed systems can generate a search result from the hybrid search index in response to receiving a search query of the hybrid search index. In some cases, the disclosed systems can rank one or more content items included in the search result based on observation layer data of the one or more content items.

The invention discloses a multi-channel integrated marketing contact content management system and method, and relates to the technical field of marketing contact content auditing, and the method comprises the steps: creating a plurality of marketing contacts in a unified management platform, and configuring a delivery channel; establishing a design specification rule base; receiving a marketing content picture uploaded by the user and associating the target channel with the contact; calling a rule base on the basis of a contact type, starting an AI auditing engine to carry out automatic compliance inspection on the picture, including preprocessing, layout identification, character extraction and character number statistics, font and character size identification, color identification and functional element detection, and comparing an identification result with a rule to generate an auditing result; and approving the delivery of compliant content and tracking the effect, and optimizing an AI engine and a rule base based on data. According to the method, AI intelligent auditing is embedded into the marketing content publishing process, multi-channel integrated management and intelligent auditing of the marketing content are achieved, the auditing efficiency and accuracy are remarkably improved, it is guaranteed that the content is standard and unified, and the labor cost is reduced.

Disclosed is an improved approach to implement natural language processing for metadata queries. The query may be applied against metadata for content stored in a cloud-based content management system.

One embodiment of a system comprises a client device and a remote content management system. The client device comprises a synchronization manager that maintains a remote virtual model that models a synchronization state of a remote peer resource at the content management system and a local virtual model that models a synchronization state of a local peer resource in the local file system. The synchronization manager determines that the remote peer resource and local peer resource are out of sync based on a comparison of the remote virtual model and the local virtual model and synchronizes changes from the local cache to the content management system to update the remote peer resource or synchronizes changes from the content management system to update the local peer resource.

This disclosure describes systems that identify one or more models (e.g., large language models and / or virtual assistants) permitted to access content items stored for user accounts within a content management system. The disclosed systems can determine a model available to a user account within the content management system from among the one or more models. For example, the disclosed systems can determine one or more relationships between the user accounts within the content management system, large language models utilized by the user accounts, virtual assistants utilized by the user accounts, and content items accessed by the user accounts. The disclosed systems can determine the model for the user account according to the one or more relationships. The disclosed systems can provide a notification corresponding to the model via a user interface of a client device associated with the user account.

The present disclosure is directed toward systems, methods, and non-transitory computer-readable media for generating a dynamic facet by using a large language model. For example, the disclosed systems extract raw facet data from a plurality of content items stored in a content management system. In addition, the disclosed systems determine one or more facet content groups by grouping the plurality of content items according to the raw facet data. Further, the disclosed systems generate a facet prompt from the one or more facet content groups. Moreover, the disclosed systems generate a dynamic facet by providing the facet prompt to a large language model.

A multimodal content management system having a block-based data structure can include an artificial intelligence (AI)-based code unit generator that can generate code units executable against the block-based data structure to provide information requested by users. For example, the code units can be generated in response to natural language prompts received via a question and answer Q&A assistant engine. A neural network can be trained on block types, block dependencies, block content values, block content types, and / or block format. The neural network can receive a set of tokens generated based on a natural language prompt and generate one or more query strings to be included in a particular code unit. The tokens can be indicative of block properties, content, or other items in the block-based data structure. The code unit can be structured to execute more than one query against the block-based data structure such that a particular result set can include content items of different modalities.

Systems and methods for controlling visibility of user identifying information. In the event that documents or records are shared between different business partners or business organizations, usernames appearing on the documents, notification or records may be selectively masked to preserve the user identity security rules.

The present disclosure relates to systems, non-transitory computer-readable media, and methods for generating and providing content update synopses using a large language model. In particular, in some embodiments, the disclosed systems determine, for a collaborative workspace of a content management system, activity metadata defining user account activity across a plurality of user accounts performing actions within the collaborative workspace. Further, the disclosed systems can generate, from the activity metadata, a text representation of the user account activity indicating the actions within the collaborative workspace that occur between a first timestamp and a second timestamp. Additionally, the disclosed systems can generate a summary generation prompt from the text representation of the user account activity. Moreover, the disclosed systems can generate an activity summary for the user account activity within the collaborative workspace between the first timestamp and the second timestamp by providing the summary generation prompt to a large language model.

Aspects of the present disclosure relate to hierarchical content organization techniques, which may thus enable improved content indexing and / or retrieval, among other benefits. In examples, a content platform maintains a content hierarchy, where, for example, each category within the content hierarchy has an associated set of categories / subcategories. It will be appreciated that any number of hierarchical levels may be used. Accordingly, a post or other content item may be associated with one or more categories / subcategories (e.g., one or more nodes) of the content hierarchy, thereby facilitating subsequent retrieval of the content (e.g., responsive to a user query and / or to provide to a search platform). Thus, in contrast to discussion boards and other content management systems, the disclosed aspects ensure content is organized when created, thereby improving later retrieval and / or any of a variety of subsequent processing, among other benefits.

We provide new technology for managing content using blockchain. [Solution] The content management system 0 includes an acquisition unit, a score calculation unit, a reception unit, and a point calculation unit. The acquisition unit acquires SNS (social networking service) information about the user's SNS. The score calculation unit calculates a credit score that indicates the user's creditworthiness based on the user's SNS information. The SNS information includes exchange relationship information regarding the user's exchange relationships on the SNS. The reception unit receives a review score for the content from the user. The point calculation unit calculates evaluation points for the user's content based on the trust score and the review score, and stores the evaluation points in the blockchain.

Examples provide record retention to content items in a content management system. The system identifies a content item stored in a content items database and displays a user interface (UI) that includes a list for a categorization criterion. User input is received from the UI indicating a user selection for the first categorization criterion. A retention mapping schedule maps the criterion options to retention labels of a retention schedule. A retention label for the content item is determined based on the first user selection and the retention mapping schedule, the retention label being defined in the retention schedule and having an expiration duration defining how long content items marked with the retention label are retained. The retention label is stored as metadata for the content item, and the content item is deleted after an expiration duration of the content item has elapsed.

This disclosure describes techniques for continuous improvement of machine learning models (also called data models) in a Content Management System (CMS). In one example, a CMS may store a set of data models for each application such as plate number recognition, facial recognition, a determination of likelihood of assault to a law enforcement officer in a traffic violation or robbery scenario, and car identification. In an example embodiment, a predictive model may be used to select a data model from the plurality of data models. The selected data model may be further improved or trained to a new sample of data features to generate an output pattern (e.g., likelihood of assault to a law enforcement officer).

The invention relates to the technical field of education management, in particular to a health education content management system for gynecological nursing, which is constructed by the following steps: S1, analyzing original medical content to generate a professional expression structure, and identifying a core medical entity and a logic relation chain between entities; s2, on the basis of the professional expression structure and the user cognition level label, outputting a cognition adaptation expression through a hierarchical conversion engine; and S3, binding the cognitive adaptation expression with a professional expression structure, and constructing a bidirectional version topological relation in a content storage library, so that a reversible mapping relation is formed between the professional expression and the adaptation expression. According to the method, not only is the insufficient adaptation of a general medical model in terms of gynecology ambiguity and multi-stage dependence overcome, but also the subsequent conversion process is ensured to keep consistent in terms, relationships and contexts, and an interpretable and traceable basic expression framework is provided for cognitive adaptation.

Disclosed are systems, methods, and non-transitory computer-readable storage media for malware detection and content item recovery. For example, a content management system can receive information describing changes made to content items stored on a user device. The content management system can analyze the information to determine if the described changes are related to malicious software on the user device. When the changes are related to malicious software, the content management system can determine which content items are effected by the malicious software and / or determine when the malicious software first started making changes to the user device. The content management system can recover effected content items associated with the user device by replacing the effected versions of the content items with versions of the content items that existed immediately before the malicious software started making changes to the user device.

A content management method, in particular a location-based, preferably decentralized, content management method, is configured at least for managing digital contents within a metaverse linked to a distributed ledger technology (DLT), such as a blockchain or a tangle, wherein a virtual space defined by the metaverse is divided into a number of segments, in particular volume segments, arranged next to one another and / or above one another, and wherein digital contents are assigned to individual segments, wherein a decentralized autonomous organization (VolumeDAO) set up on the DLT is assigned to at least one of the segments.

This disclosure describes techniques for continuous improvement of machine learning models (also called data models) in a Content Management System (CMS). In one example, a CMS may store a set of data models for each application such as plate number recognition, facial recognition, a determination of likelihood of assault to a law enforcement officer in a traffic violation or robbery scenario, and car identification. In an example embodiment, a predictive model may be used to select a data model from the plurality of data models. The selected data model may be further improved or trained to a new sample of data features to generate an output pattern (e.g., likelihood of assault to a law enforcement officer).

A content management system synchronizes content items across client computing systems connected by a network. Each client device has a storage allocation for synchronized shared content items. If the storage allocation for shared content items on a client device is exceeded by the request to add or edit a content item such that it is enlarged, or open a large content item remote to the client device, a client application or the host of content management system selects content items to remove from residence on the client device but keep remotely on content management system. Upon removal of the selected content items, the client application creates shadow items, representing the content item but only containing the metadata of the content item. This creates sufficient space for the initial request to be completed while maintaining user access to all synchronized shared content items.

This content management system comprises: an acquisition unit (503B) that acquires product identification information of a product to be purchased, and information indicating whether or not additional work is to be performed on the product based on a request from the purchaser of the product; a work time storage unit that stores the product identification information in association with the additional work time required for the additional work; an estimation unit (506B) that estimates a total work time on the basis of the bagging time for bagging the product to be purchased and the additional work time required for the additional work to be performed on the product to be purchased that requires additional work; a storage unit (502B) that stores content and the playback time of the content; an extraction unit (507B) that extracts content corresponding to the total work time from the storage unit; and a content provision unit (508B) that displays, on a display device visible to a customer, the extracted content.