133 results about "Item Collection" patented technology

An online system automatically generates a personalized collection of items around a theme. The online system generates a prompt for input into a language model, the prompt including information about a plurality of items and a text describing the theme around which the collection of items will be built. The online system requests the language model to generate, based on the prompt, a list of products eligible for building the collection of items. The online system accesses a computer model trained to identify a set of items personalized for a user of the online system. The computer model identifies, based on the list of eligible products and information about the user, the set of items for populating the collection of items. The online system causes a device of the user to display a user interface with the collection of items for inclusion into a cart of the user.

The invention discloses an emergency patient intelligent pre-examination triage system, and particularly relates to the field of emergency patient pre-examination triage, comprising: a data processing module performs standardization processing on patient chief complaint text and sign data, and constructs a pre-examination data set; the disease prediction module inputs the pre-examination data set into a multi-label disease prediction model, and outputs a potential disease set and a prediction probability thereof; the probability adjustment module performs confidence correction on the prediction result in combination with the historical medical history of the patient; the graph construction module constructs a potential disease semantic adjacency graph according to the semantic similarity; the detection item determination module performs co-occurrence path compression on the basis of the semantic graph structure, extracts a minimum detection item set and generates an auxiliary detection item list; the triage guidance module schedules and ranks the detection items according to the real-time states of the detection resources, triage detection guidance is generated, and efficient and flexible emergency treatment primary screening planning is achieved.

The invention relates to the technical field of application of the Internet of Things, in particular to a food safety traceability method and system based on the Internet of Things, solves the problems of a traditional food safety traceability method, improves the overall efficiency and effect of food safety management, and provides technical support for food safety. The method comprises the following steps: performing safety detection on food to obtain a food safety quality detection set; comparing the food safety quality detection set with a food safety quality standard set, and extracting and summarizing items with detection results exceeding the standard to obtain a food safety exceeding item set; for each standard-exceeding item, extracting a food stage correlation vector corresponding to the standard-exceeding item from a preset item stage correlation database; and calculating a processing stage correlation coefficient sum, a transportation stage correlation coefficient sum, a storage stage correlation coefficient sum and a sales stage correlation coefficient sum in all the food stage correlation vectors, and sorting the stages according to calculation results.

Provided in the present application are a sample processing method and apparatus for a cross-domain recommendation model, and a device and a storage medium. The method comprises: acquiring a plurality of recommended projects in a target domain; fusing a first interaction feature of a sample object in a source domain with a second interaction feature of the sample object in the target domain, so as to obtain a fused interaction feature of the sample object; determining a similarity index between the fused interaction feature and each recommended project; on the basis of the similarity index, screening the plurality of recommended projects to obtain a plurality of strong negative samples, and combining the plurality of strong negative samples into a candidate recommended project set; fusing a third interaction feature of an interaction behavior having the timeliness of the sample object in the source domain with a fourth interaction feature which represents a clustering center of the second interaction feature, so as to obtain a migration interaction feature of the sample object; and on the basis of a similarity index between the migration interaction feature and each recommended project in the candidate recommended project set, screening the plurality of strong negative samples to obtain a real strong negative sample.

The invention relates to the technical field of recording and broadcasting teaching, and discloses a recording and broadcasting teaching course quality evaluation method based on cloud computing. The method comprises five steps of data item collection, data preprocessing, evaluation model construction, evaluation strategy optimization and quality optimization. Wherein the evaluation model construction adopts a dynamic heterogeneous improved graph calculation method, and evaluation reference data is obtained through the steps of construction of an evaluation heterogeneous graph, dynamic updating of a graph structure, construction of a three-layer layering weight mechanism and the like; the evaluation strategy optimization adopts a multi-objective guide improved multi-layer strategy optimization method, and optimal strategy reference data is obtained through the steps of improving a state parameter space, modeling a multi-layer strategy network and the like; and finally obtaining a course quality comprehensive optimization reference scheme. According to the method, multi-modal dynamic data can be comprehensively processed, correlation of each factor is deeply mined, multi-objective optimization is balanced, evaluation accuracy and effectiveness are improved, and specific guidance is provided for quality improvement of recording and broadcasting courses.

The invention provides a cross-modal collaborative recommendation method and system based on a large language model. The method comprises the steps of obtaining identity information of a user and a to-be-recommended item set; inputting the identity information and the item set into a preset recommendation model, so that the recommendation model predicts the click rate of each item in the item set according to the identity information, and outputting an item recommendation list according to the click rate of each item; wherein the recommendation model is constructed on the basis of a large language model and is obtained through training by using a training data set, and the training data set is based on the large language model and a collaborative filtering technology. And the text data of the recommendation fields and the user-project interaction data are constructed after prompt sequence conversion, feature mapping and feature fusion, so that the project recommendation accuracy of the large language model is improved.

In various examples, session-based recommender model systems and applications are disclosed. Systems and methods are disclosed that use a cosine similarity loss during the training of a machine learning model to train the model to generate an item recommendation based on predicting a next item from a sequence of prior items selected within a session. A recommendation model is trained based on training data that represent an ordered sequence of user interactions with the set of items. A set of item embeddings is generated for the set of items. The recommendation model is trained to predict a session embedding that represents a user behavior pattern from a sequence of item embeddings. A cosine similarity loss computed from the session embedding and the item embeddings is used to train the recommendation model. The cosine similarity loss may include both positive and negative cosine similarity components.

An online system receives a request to access an interactive geographical map of sources from a client device associated with a user. The system retrieves data describing a geographical location associated with the user. The system identifies one or more sources within a threshold distance of the location and retrieves data including information describing items available at each source. For each source, the system accesses and applies a machine-learning model to predict a user engagement score indicating a likelihood of one or more interactions by the user with a set of items available at the source if the source is included in the map. Based on the score for each source, the system selects a set of sources and generates the map, in which the map indicates the geographical location of each selected source. The map is then sent to the client device, causing the device to display the map.

The invention discloses a digital tourist tourism planning system, and relates to the technical field of tourism planning. The system comprises an information acquisition unit, a preference recommendation unit, a path planning unit and a visual display unit. Wherein the information acquisition unit is used for acquiring tourist basic information, target scenic spot related information and traffic information; the preference recommendation unit is used for constructing a preference recommendation algorithm, performing content recommendation based on the tourist basic information and the target scenic spot related information, and determining a scenic spot recommendation item set; the path planning unit is used for selecting tourism living points and scenic spot recommendation items, performing path recommendation according to current traffic information and a path planning algorithm, and performing sorting and real-time updating on planned paths; and the visual display unit is used for performing visual display by taking the scenic spot recommendation item as a first-level option interface and taking the current planned route as a second-level option interface. According to the invention, dynamic planning can be realized, and tourism planning rationality of tourists is improved.

The present invention relates to the technical field of intelligent logistics management and control. Disclosed are a human-machine collaborative management and control method, system and device involving logistics storage and transportation. The method comprises: on the basis of a logistics storage and transportation task, determining a target operation process and a corresponding target operation item queue; executing said task on the basis of the queue; determining whether the queue belongs to a manual operation item set; if the queue belongs to the manual operation item set, generating and issuing a manual operation notification instruction; determining whether a confirmation signal fed back on the basis of the manual operation notification instruction is received; if yes, updating the state of operation items to 'in progress'; determining whether the queue belongs to a feedback operation item set; if the queue belongs to the feedback operation item set, determining whether a manual feedback completion signal is received; if yes, updating the state of the operation items to 'completed'; and when the label of one of the operation items is the maximum label in the queue, confirming that said task is completed. According to the present invention, an instruction is sent to an operator and a manual feedback signal is received in time, so as to collaboratively manage and control the logistics storage and transportation operation process requiring manual participation.

The invention relates to the technical field of computer software, and discloses a code submission method, a code submission system, computer equipment and a storage medium, and the method comprises the steps: setting a to-be-tested verification item set which must be verified, and setting a secret key generated by an ID number corresponding to a newly submitted code to carry out the encryption and decryption of a verification result, according to the method, authenticity and accuracy of verification results can be ensured, and it is judged that newly submitted codes are allowed to be merged only when research and development personnel really complete each test verification item and the verification result corresponding to each test verification item is successful, so that the quality and efficiency of code submission can be remarkably improved, and the efficiency of code submission is improved. Meanwhile, development work of each stage can be fully verified and monitored, various problems caused by code submission errors can be effectively reduced, the overall stability and reliability of a project are improved, and smooth promotion of the project is guaranteed.

The invention provides an adaptive knowledge contrast learning recommendation method based on a dynamic attention network. The method comprises the following steps: step 1, acquiring a user-project interaction graph and a knowledge graph; wherein the user-project interaction graph is used for describing historical interaction records of a user on projects, and the knowledge graph describes a relationship between the projects in a triple form; step 2, constructing an AKCL-DA network framework, and training the AKCL-DA network framework by using the user-project interaction graph and the knowledge graph to obtain a recommendation model; 3, inputting the target user-project interaction diagram into the recommendation model, and generating a recommendation result of the project of the target user; the item recommendation result is an item set with a high matching score output by the recommendation model. According to the method, the AKCL-DA network framework is provided to obtain the recommendation model, and the problem that sparse information and personal interests are not matched with general knowledge in the knowledge graph can be solved.

An online concierge system receives an order including one or more items from a client device associated with a user and retrieves user data for the user. The system accesses and applies a machine-learning model to predict a measure of preference of the user associated with each item category associated with the items based on the user data and identifies an item associated with at least a threshold predicted measure of preference. The system retrieves picker data for a picker assigned to collect the items and predicts a level of expertise of the picker associated with collecting the identified item based on the picker data. If the predicted level of expertise is less than a threshold, the system identifies an expert picker based on picker data for the expert picker and sends a prompt to a client device associated with the expert picker to assist with collecting the identified item.

Methods and systems are disclosed for sharing collections of content items in chat sessions. The methods and systems receive a request to share a first content item and present a GUI comprising a first set of options and a second set of options, the first set of options being associated with adding the first content item to a collection of content items that is accessible to a plurality of recipients, the second set of options being associated with sending the first content item to individual recipients. The methods and systems determine a set of target recipients of the first content item and select a content sharing link between a first link to the collection of content items and a second link directly to the first content item. The methods and systems send, to a target recipient, the content sharing link that has been selected.

The invention relates to the technical field of data processing, and provides a medical article expiration date management system based on machine learning, and the system comprises a data obtaining module which is used for obtaining the article information of a to-be-managed medical article and the warehouse information of warehouses of all grades; the first calculation module is used for processing the article information through a machine learning model and predicting the usage amount and the valid period turnover rate of the medical articles; the first strategy module is used for determining a picking strategy for the medical articles according to the usage amount and the effective period turnover rate of the medical articles; the second strategy module is used for determining a deployment strategy for the medical articles according to the stock of the medical articles in the warehouses of all levels and the first expiry date turnover rate; the first management module is used for ordering and getting the medical articles according to the article getting strategy; and the second management module is used for deploying the medical articles according to the deploying strategy. According to the invention, the accuracy of medical article validity period management and medical article receiving and purchasing can be improved.

To provide an exposure information provision system, exposure information provision method and program, which makes it easy to grasp exposure information of Web articles.SOLUTION: An exposure information provision system 1 is provided, comprising an exposed item collection unit 11 capable pf performing processing for collecting multiple Web articles matching a keyword, a group generation unit 15 capable of performing processing for generating groups with two or more Web articles based on the collected multiple Web articles, and an output unit 12 capable of performing processing for outputting a list of the groups.SELECTED DRAWING: Figure 3

Methods and systems are disclosed for sharing collections of content items in chat sessions. The methods and systems receive a request to share a first content item and present a GUI comprising a first set of options and a second set of options, the first set of options being associated with adding the first content item to a collection of content items that is accessible to a plurality of recipients, the second set of options being associated with sending the first content item to individual recipients. The methods and systems determine a set of target recipients of the first content item and select a content sharing link between a first link to the collection of content items and a second link directly to the first content item. The methods and systems send, to a target recipient, the content sharing link that has been selected.

The invention belongs to the technical field of data processing. The invention provides a complete-set material management and control method and system and computer equipment, and the method comprises the steps: building a bidirectional correlation index of a suite and subitems, and carrying out the correlation display of the to-be-purchased suite and the subitems according to the bidirectional correlation index when a suite purchasing application is received; according to received purchase order arrival information, generating arrival traceability codes of arrival subitems; according to a received suite receiving application, determining subitems of the suite according to the bidirectional association index, and according to traceability codes of the determined subitems and an approved receiving application form, determining a to-be-delivered suite and updating a suite inventory; and when a sub-item receiving application is received, according to the arrival traceability code of the sub-item and the approved receiving application form, determining the sub-item to be delivered and updating the sub-item inventory at the same time, and according to the bidirectional association index and the updated sub-item inventory, updating the kit inventory, thereby improving the inventory utilization efficiency and the receiving accuracy.

An example method includes receiving a request to identify a set of media items for playback to a user. The method further includes providing information about the request to a diffusion model (DM) component and receiving, from the DM component, a set of vectors corresponding to the information about the request. The method also includes selecting, using a different component, a set of media items based on the set of vectors, and presenting information about the set of media items to the user.

The invention provides an interaction method and device, equipment, a storage medium and a product, and relates to the technical field of computers. The method comprises the steps that a preset category label set and an object information set are displayed in an information display page associated with a live video interface, the object information set comprises object information of a preset object, and in response to a trigger operation for a target preset category label, a corresponding preset screening item set is displayed, the preset screening item is determined according to a preset service attribute dimension of a preset category label, displaying a corresponding candidate item set in response to a trigger operation for a target preset screening item, and updating and displaying the object information set in response to a trigger operation for a target candidate item. The updated object information set comprises object information of a preset object meeting a first screening condition, and the first screening condition is determined according to the target preset category label and the target candidate item. Through adoption of the technical scheme, the interaction efficiency in the live broadcast scene can be effectively improved.

The invention provides a surveying and mapping project risk identification method and system, and a medium. The method comprises the following steps: obtaining a to-be-supervised project in a current surveying and mapping project set; the to-be-supervised items at least comprise initial risk items; the initial risk item is at least one surveying and mapping item meeting a plurality of preset risk judgment rules in a current surveying and mapping item set; constructing a risk project supervision library based on the to-be-supervised project; the risk project supervision library comprises each to-be-supervised risk project. According to the surveying and mapping project risk identification method and system and the medium, the surveying and mapping project with the supervision risk can be rapidly identified and extracted from massive surveying and mapping projects, so that targeted supervision can be performed on the surveying and mapping project with the supervision risk, and the allocation rationality of supervision resources is improved.

The invention discloses a page interaction method and device, equipment, a medium and a product. The method comprises the following steps: displaying an information board of a live broadcast item on a live broadcast page; wherein when the inventory of the selected supply site of the live broadcast article does not meet the supply condition, information used for prompting switching of the supply site is displayed in a decision interaction area in the information board; in response to a trigger operation in the decision interaction area, displaying an article collection interface in the live broadcast page, and displaying a site switching pop-up window on the upper layer of the article collection interface; wherein an article set corresponding to the selected supply site is displayed in the article set interface, and the site switching pop-up window is used for prompting to switch to a target supply site of which the stock of live broadcast articles meets the supply condition; and in response to the confirmation operation of the station switching pop-up window, switching and displaying the article set of the target supply station in the article set interface, so that flexible matching of supply and demand resources is realized, and balanced distribution of the supply and demand resources is ensured.

The present invention provides a reservation method, device, equipment and storage medium. The method includes: obtaining N reservation items; inputting the N reservation items into a preset mapping table for query to determine a reservation item set; determining the first reservation time corresponding to each first reservation item according to the mapping relationship between the first reservation items in the reservation item set; and displaying a reservation item list. In an embodiment of the present invention, after obtaining the user's reservation items, query the reservation items in the preset mapping table to determine the reservation item set; further, according to the mapping relationship between the reservation items in the reservation item set, determine the reservation time corresponding to each reservation item, and display it in the reservation item list, so as to reasonably arrange the reservation time corresponding to each reservation item for the user, avoid conflicts in reservation time between reservation items, reduce the waiting time of the user during the reservation process, and thus improve the efficiency of the reservation.

Disclosed embodiments provide systems and methods related to collecting return items using an automated kiosk based on a real time risk decision. The automated kiosk captures return item information representing a return item and transmits the return item information and a request for return risk level relating to the return item to a server operable to execute a machine learning model trained on historical information to determine the risk level. The server determines the risk level based on the received return by using the machine learning model and transmits the determined risk level to the kiosk in real-time. Based on the determined risk level and a return amount associated with the return item, the server may also process a refund in real-time.

Systems and methods are described for disambiguating user input based on a physical location of items in a vicinity of a user. The system determines that a query received from a user contains an ambiguity. In response, the system identifies several items in the physical vicinity of the user. Then, the system analyzes the identified plurality of items to determine whether the plurality of items forms a first ensemble of items or a second ensemble of items. If the plurality of items forms a first ensemble of items, the system performs a search using the search query and a first keyword related to the first ensemble of items. If the plurality of items forms a second ensemble of items, the system performs a search using the search query and a second keyword related to the second ensemble of items. The system then outputs results of the performed search.

The embodiment of the invention relates to a to-be-detected item typesetting method and device, electronic equipment and a storage medium, and the method comprises the steps: under the condition that a target set type is an enzyme immunoassay item set, according to preset enzyme immunoassay strategy information and item names corresponding to all to-be-detected items, setting the to-be-detected items according to the preset enzyme immunoassay strategy information; performing layout sorting on each experiment number corresponding to the plurality of items to be detected, and adding a fixed position before the first experiment number and / or after the last experiment number of each item to be detected, so as to generate a first layout file suitable for the microplate reader; under the condition that the target set type is a fixed electrophoresis type item set, according to preset electrophoresis typesetting information, item names corresponding to all the to-be-detected items and the number of experiment numbers contained in all the to-be-detected items, experiment numbers contained in all the to-be-detected items are distributed, and generating a second layout file suitable for the immunofixation electrophoresis apparatus. The processing efficiency of to-be-detected items can be improved, and the risk of manual operation errors is reduced.

A method for graph neural network-based recommendation is disclosed. The method comprises the following steps: receiving a user-project bipartite graph, wherein the user-project bipartite graph comprises a user node set representing a user set, a project node set representing a project set, and an edge set representing interaction between users and projects; obtaining user embedding of each user in the user set and project embedding of each project in the project set; performing an intra-layer aggregation process to generate an aggregated user embedding of each user in the user set and an aggregated item embedding of each item in the item set based on different weight coefficients of each user and each item; executing an interlayer propagation process to generate a propagation user embedding of each user in the user set and a propagation item embedding of each item in the item set based on different weight coefficients of each propagation layer; and making recommendations for the users in the user set based on the propagation user embedding and the propagation item embedding.

The invention discloses a project transaction pushing method and system based on artificial intelligence, and belongs to the technical field of semantic modeling and graph neural networks. Project information submitted by at least one project party is collected, and text description of the project information is converted into semantic vectors; historical investment records and preference information of multiple capital parties are collected, and a multi-dimensional semantic preference vector is constructed; inputting the preference vector into a pre-training graph neural network model, and performing mapping and enhancement on a transverse semantic association relationship between the items; short-term interest features are extracted in combination with the current active state, the recent behavior and the fund flow condition of the capital party, and the short-term interest features are fused with long-term preferences to generate a dynamic weight vector; performing weighted sorting on the items based on the priority score and the dynamic weight, and outputting a personalized candidate item set; according to the method, the accuracy, timeliness and individuation degree of project matching are improved, and the method has good popularization value.

The invention is applicable to the technical field of recommendation, and provides a collaborative filtering recommendation method based on double popularity constraints, which comprises the following steps of: firstly, constructing a user item score table and an item attribute relation table; secondly, obtaining normalized item popularity and normalized attribute popularity, and obtaining constraint factors by using double popularity; performing similarity calculation by using a dual popularity constraint factor and a Pearson similarity formula to obtain adjacent users of the target user; according to the scoring information of the adjacent users of the target user, performing prediction scoring on the item set which is not scored by the target user to obtain a prediction scoring table of the target user; and finally, extracting first N items with the highest score value from the prediction score table as recommendation results and providing the recommendation results to the target user. According to the method, by constraining the item popularity and the attribute popularity, the popularity deviation is relieved, and the long-tail effect is relieved.

The invention provides a page display method and device, equipment, a storage medium and a product, and relates to the technical field of computers. The method comprises the steps that an information input item set is displayed in a first area in a preset page, preset media content is displayed in a second area in the preset page, and the preset media content comprises image information related to at least one information input item. According to the technical scheme, the information input item set and the image information related to the at least one information input item are displayed in the same page at the same time, the related image information of the information input item can be displayed more visually and vividly, a user is helped to know the information input item more comprehensively, and the user experience is improved. And the information input efficiency, accuracy and success rate are improved.