摘要：【中文】本申请提供一种资讯推荐方法及装置，涉及互联网技术领域，能够提高资讯推荐结果的准确性和多样性。该方法包括：获取用户组中多个用户的多个特征标签、资讯组中多个资讯的多个属性标签、用户组中用户的交互信息，以及资讯组中资讯的交互信息；其中，用户的交互信息用于表征用户浏览的多个资讯，资讯的交互信息用于表征资讯被多个用户浏览；利用用户组中的第一目标用户的交互信息以及第一目标用户浏览的多个资讯的属性标签，构建用户‑资讯偏好模型；用户‑资讯偏好模型用于为第一目标用户推荐资讯；利用资讯组中的第一目标资讯的交互信息以及特征标签，构建资讯‑用户受众模型；利用资讯‑用户受众模型将第一目标资讯推荐给用户组中的用户。 【EN】The application provides an information recommendation method and device, relates to the technical field of internet, and can improve accuracy and diversity of information recommendation results. The method comprises the following steps: acquiring a plurality of feature tags of a plurality of users in a user group, a plurality of attribute tags of a plurality of information in an information group, interactive information of the users in the user group and interactive information of the information in the information group; the interactive information of the information is used for representing the information browsed by the users; constructing a user-information preference model by using interactive information of a first target user in a user group and attribute tags of a plurality of information browsed by the first target user; the user-information preference model is used for recommending information for the first target user; constructing an information-user audience model by using the interactive information and the feature labels of the first target information in the information group; the first target information is recommended to users in the user group using an information-user audience model.

摘要：【中文】本发明提供了一种基于加密算法的模型构建方法及相关设备，涉及机器学习技术领域，通过获取原始数据集，原始数据集包含多个原始数据，每个原始数据包含多维特征；确定原始数据集对应的数据分布特性，数据分布特性表征各个原始数据中每一维特征的分布状况；依据数据分布特性，确定原始数据集对应的映射规则；对原始数据集中的各个原始数据进行预处理，并应用映射规则对预处理后的各个原始数据进行映射，得到各个原始数据对应的训练数据；应用预先设置的全同态加密算法对各个训练数据进行加密；应用加密后的训练数据对初始模型进行训练，得到目标模型，所述初始模型为待训练模型。能够避免密文膨胀的缺陷，提升模型的训练效率。 【EN】The invention provides a model construction method based on an encryption algorithm and related equipment, and relates to the technical field of machine learning, wherein an original data set is obtained and comprises a plurality of original data, and each original data comprises a multi-dimensional feature; determining data distribution characteristics corresponding to the original data set, wherein the data distribution characteristics represent the distribution condition of each dimension feature in each original data; determining a mapping rule corresponding to the original data set according to the data distribution characteristics; preprocessing each original data in the original data set, and mapping each preprocessed original data by applying a mapping rule to obtain training data corresponding to each original data; encrypting each training data by using a preset fully homomorphic encryption algorithm; and training the initial model by using the encrypted training data to obtain a target model, wherein the initial model is a model to be trained. The defect of ciphertext expansion can be avoided, and the training efficiency of the model is improved.

摘要：【中文】本发明提供一种基于SPARK的用户资讯个性化分析方法、装置及系统，包括：第一服务器确定多维度的用户特征信息与资讯标签的关联程度、用户特征信息的类型，按照类型将用户特征信息、资讯标签、关联程度存入映射表中，将用户特征信息和类型标识存入特征标识表中并将其广播到SPARK平台的各个节点中，获取实际的多维度的用户特征信息并广播到SPARK平台的各个节点中；SPARK平台的各个节点将实际的多维度的用户特征信息转换为RDD，根据RDD、映射表和特征标识表进行多维度的用户特征信息向资讯标签的映射，基于映射生成个性化分析数据输出至第一服务器。该方案可以在资讯服务上线时就为用户提供个性化服务，提高客户体验度。 【EN】The invention provides a SPARK-based user information personalized analysis method, device and system, comprising the following steps: the first server determines the relevance degree of multi-dimensional user characteristic information and an information label and the type of the user characteristic information, stores the user characteristic information, the information label and the relevance degree into a mapping table according to the type, stores the user characteristic information and the type identification into a characteristic identification table and broadcasts the user characteristic information and the type identification to each node of the SPARK platform, and obtains the actual multi-dimensional user characteristic information and broadcasts the actual multi-dimensional user characteristic information to each node of the SPARK platform; each node of the SPARK platform converts actual multidimensional user characteristic information into RDD, mapping the multidimensional user characteristic information to the information label according to the RDD, the mapping table and the characteristic identification table, and generating personalized analysis data based on the mapping and outputting the personalized analysis data to the first server. The scheme can provide personalized service for the user when the information service is on line, and improves the experience degree of the user.

摘要：【中文】本说明书实施例公开了一种资讯推荐装置、方法、设备及系统。所述装置包括批量处理模块和实时处理模块，所述批量处理模块用于获取目标用户的特征信息，构建用户偏好模型并将其发送至实时处理模块；所述实时处理模块用于获取资讯、资讯在各个类别标签的权重信息以及用户对资讯各个类别标签的偏好信息，并基于权重信息和偏好信息确定推荐值向用户推荐资讯；还用于监听kafka队列消息，确定kafka队列消息中存在模型更新的消息时，更新偏好模型，并基于更新后的模型确定推荐值。利用本说明书实施例不仅可以根据用户对资讯的喜好程度推荐资讯，而且可以及时对用户的兴趣变化作出响应，从而可以保证推荐结果合理、准确的同时，提高用户体验。 【EN】The embodiment of the specification discloses an information recommendation device, method, equipment and system. The device comprises a batch processing module and a real-time processing module, wherein the batch processing module is used for acquiring the characteristic information of a target user, constructing a user preference model and sending the user preference model to the real-time processing module; the real-time processing module is used for acquiring information, weight information of the information on each type label and preference information of a user on each type label of the information, and determining a recommendation value to recommend the information to the user based on the weight information and the preference information; and the system is also used for monitoring the kafka queue messages, updating the preference model when determining that the messages with updated models exist in the kafka queue messages, and determining the recommended value based on the updated models. By using the embodiment of the specification, the information can be recommended according to the preference degree of the user to the information, and the interest change of the user can be responded in time, so that the reasonable and accurate recommendation result can be ensured, and the user experience is improved.

摘要：【中文】本发明公开了一种基于结构化流的流式计算指标生成系统，该系统包括：数据源管理模块、指标逻辑定义模块、输出渠道管理模块以及流式计算上下文模块；所述数据源管理模块用于根据用户的流式计算指标生成指令输出对应的数据源；所述指标逻辑定义模块用于根据用户的流式计算指标生成指令输出对应的处理逻辑；所述输出渠道管理模块用于根据用户的流式计算指标生成指令输出对应的输出渠道；所述流式计算上下文模块用于根据所述数据源管理模块输出的数据源、所述指标逻辑定义模块输出的处理逻辑以及所述输出渠道管理模块输出的输出渠道生成流式计算指标。本发明提高了流式计算指标的开发效率，降低了开发成本。 【EN】The invention discloses a stream type calculation index generation system based on structured stream, which comprises: the system comprises a data source management module, an index logic definition module, an output channel management module and a streaming computing context module; the data source management module is used for generating an instruction according to the streaming calculation index of the user and outputting a corresponding data source; the index logic definition module is used for generating an instruction according to the streaming calculation index of the user and outputting a corresponding processing logic; the output channel management module is used for generating an instruction according to the streaming calculation index of the user and outputting a corresponding output channel; the stream type computation context module is used for generating stream type computation indexes according to the data source output by the data source management module, the processing logic output by the index logic definition module and the output channel output by the output channel management module. The invention improves the development efficiency of the stream type calculation index and reduces the development cost.

摘要：【中文】本申请提供了一种流式计算指标的生成方法及装置，首先从数据流中接收待处理的多个目标数据源；接收用户发送的目标处理逻辑，所述目标处理逻辑包括所述多个目标数据源的之间的处理逻辑；接着将所述目标处理逻辑转换为标准处理逻辑；然后将所述多个目标数据源和标准处理逻辑组合得到指标业务清单；根据所述指标业务清单生成流式计算指标，以便进行数据流的处理。如此，通过对目标数据源和目标处理逻辑进行转换，得到标准的指标业务清单，并根据指标业务清单自动生成流式计算指标，业务开发人员无需掌握结构化流技术也能完成指标的开发，提高了开发效率。 【EN】The application provides a method and a device for generating streaming computation indexes, which comprises the steps of firstly receiving a plurality of target data sources to be processed from a data stream; receiving target processing logic sent by a user, wherein the target processing logic comprises processing logic among the plurality of target data sources; then converting the target processing logic into standard processing logic; then combining the multiple target data sources and the standard processing logic to obtain an index service list; and generating a stream type calculation index according to the index service list so as to process the data stream. Therefore, a standard index service list is obtained by converting the target data source and the target processing logic, and the stream type calculation index is automatically generated according to the index service list, so that a service developer can complete the development of the index without mastering a structured stream technology, and the development efficiency is improved.

摘要：【中文】本申请实施例提供一种微服务架构的健康检查方法及装置，方法包括：调取目标微服务架构系统对应的健康检查组件，其中，所述健康检查组件包括预设的健康检查核心组件和接收到的用户自定义的可插拔健康检查组件；应用所述健康检查组件对所述目标微服务架构系统对应的各个目标服务组件分别进行健康检查，得到各个所述目标服务组件各自对应的健康检查结果；判断各个所述目标服务组件各自对应的健康检查结果是否均符合预设健康条件，若是，则基于预设的调度规则对各个所述目标服务组件进行调度处理。本申请能够采用无侵入方式有效实现对微服务架构系统中的服务组件的健康检查，以有效减少针对现有系统的代码改造。 【EN】The embodiment of the application provides a health check method and a health check device for a micro-service architecture, wherein the method comprises the following steps: calling a health check component corresponding to a target micro-service architecture system, wherein the health check component comprises a preset health check core component and a received user-defined pluggable health check component; respectively carrying out health check on each target service component corresponding to the target micro-service architecture system by applying the health check component to obtain a health check result corresponding to each target service component; and judging whether the health check results corresponding to the target service components all accord with preset health conditions, if so, scheduling the target service components based on preset scheduling rules. The method and the system can effectively realize the health check of the service components in the micro-service architecture system in a non-invasive mode so as to effectively reduce the code transformation aiming at the existing system.

摘要：【中文】本说明书实施例提供一种测试数据生成方法、装置、设备及存储介质。所述方法包括：获取第一测试数据表，所述第一测试数据表包括第一字段，所述第一字段与第二测试数据表中的第二字段具有关联性；从指定数据集合中选取数据对所述第一字段进行填充，所述指定数据集合包括所述第二字段下的数据。通过上述方法，在需要生成测试数据时，在第一测试数据表中区分出第一字段。在针对第一测试数据表生成测试数据时，在指定数据集合中选取出数据填充至对应的第一字段中，而所述指定数据集合中还包含有第二测试数据表中第二字段下的数据，从而使得所述第一字段与第二字段之间能够具有关联性，进而使得所生成的测试数据能够更加满足实际测试过程的需求。 【EN】The embodiment of the specification provides a test data generation method, a test data generation device, test data generation equipment and a storage medium. The method comprises the following steps: acquiring a first test data table, wherein the first test data table comprises a first field, and the first field and a second field in a second test data table have relevance; and selecting data from a specified data set to fill the first field, wherein the specified data set comprises the data under the second field. By the method, when the test data needs to be generated, the first field is distinguished in the first test data table. When test data are generated aiming at a first test data table, data are selected from a specified data set and filled into a corresponding first field, and the specified data set also comprises data under a second field in a second test data table, so that the first field and the second field can have relevance, and the generated test data can meet the requirements of an actual test process.

摘要：【中文】本发明涉及自动化物流领域，具体涉及AGV的机械安全设计。本发明是通过以下技术方案得以实现的：一种适用于AGV的机械防撞装置，包含基板，其特征在于：所述基板上安装有低位防撞装置，所述低位防撞装置包含与所述基板连接的外围板、一端与所述基板连接另一端与所述外围板的内表面抵触的弹力支撑件和两端分别与所述外围板不同位置连接的连接绳，所述连接绳包含绳体，所述低位防撞装置还包含传感器，所述传感器包含供所述绳体穿过的通过口。本发明的目的是提供一种适用于AGV的机械防撞装置和一种AGV，采用机械式检测，结构简单，使用成本可控，且对低位防护效果佳。 【EN】The invention relates to the field of automation logistics, in particular to a mechanical safety design of an AGV. The invention is realized by the following technical scheme: the utility model provides a mechanical buffer stop suitable for AGV, contains the base plate, its characterized in that: install low level buffer stop on the base plate, low level buffer stop contain with base connection's peripheral slab, one end with the base connection other end with the elastic support piece that the internal surface of peripheral slab contradicts and both ends respectively with the connection rope that the different positions of peripheral slab are connected, it contains the rope body to connect the rope, low level buffer stop still contains the sensor, the sensor contains the confession the mouth that passes through that the rope body passes. The invention aims to provide a mechanical anti-collision device suitable for an AGV and the AGV.

摘要：【中文】本发明公开了一种资讯分类模型的训练方法及装置，采集训练资讯，得到训练资讯集；对训练资讯集中的训练资讯进行多类别标注；对多类别标注后的训练资讯集进行切词和过滤，得到训练词集；将训练词集作为输入，根据改进朴素贝叶斯模型进行模型训练，得到资讯分类模型。可见，本发明的资讯分类模型通过多类别标注后的训练资讯集进行模型训练，最终资讯分类模型得到的输出结果是输入资讯属于不同资讯类别的概率，而不是像现有技术一样直接将资讯标定为某一资讯分类，不考虑资讯内容包含的其他分类内容，本发明的资讯分类更加清楚准确。 【EN】The invention discloses a training method and a device of an information classification model, which are used for acquiring training information to obtain a training information set; marking the training information in the training information set in multiple categories; performing word segmentation and filtering on the training information sets labeled by the multiple classes to obtain training word sets; and taking the training word set as input, and carrying out model training according to the improved naive Bayesian model to obtain an information classification model. Therefore, the information classification model of the invention carries out model training through the training information set labeled by multiple classes, and the output result obtained by the information classification model is the probability that the input information belongs to different information classes, rather than directly labeling the information as a certain information classification like the prior art, and other classification contents contained in the information content are not considered, so that the information classification of the invention is more clear and accurate.