摘要：【中文】本发明提供了一种用户画像的构建方法及装置，其中，该方法包括：获取目标用户在多个上网渠道上的舆情特征信息，以及所述目标用户的属性特征信息；根据所述舆情特征信息和所述属性特征信息采用预设分类器构建所述目标用户的用户画像，其中，所述预设分类器包括第一分类器和第二分类器。通过本发明，解决了现有技术中构建的用户画像不准确的技术问题，提高了用户画像的准确性和清晰度。 【EN】The invention provides a user portrait construction method and a user portrait construction device, wherein the method comprises the following steps: the method comprises the steps of obtaining public opinion characteristic information of a target user on a plurality of internet channels and attribute characteristic information of the target user; and constructing the user portrait of the target user by adopting a preset classifier according to the public opinion characteristic information and the attribute characteristic information, wherein the preset classifier comprises a first classifier and a second classifier. By the method and the device, the technical problem that the user portrait constructed in the prior art is inaccurate is solved, and the accuracy and the definition of the user portrait are improved.

摘要：【中文】一种数据获取方法，所述方法包括：接收携带有关键词的数据获取请求；根据所述关键词，从缓存中获取与所述关键词对应的可扩展标记语言文件，以及获取待读取文件；使用超文本标记语言解析器解析所述可扩展标记语言文件，获得所述可扩展标记语言文件中每种类型的数据的配置信息；从所述配置信息中获取预设键，并根据所述配置信息以及所述预设键，获得键值对；将所述键值对读入缓存中；从所述缓存中读取所述键值对，并根据所述键值对确定数据读取格式，以及依据所述数据读取格式，从所述待读取文件中读取目标数据。本发明还提供一种数据获取装置、电子设备及存储介质。本发明能提高文件的读取效率，同时，系统资源利用率较高。 【EN】A method of data acquisition, the method comprising: receiving a data acquisition request carrying a keyword; according to the keywords, obtaining extensible markup language files corresponding to the keywords from a cache, and obtaining files to be read; analyzing the extensible markup language file by using a hypertext markup language analyzer to obtain configuration information of each type of data in the extensible markup language file; acquiring a preset key from the configuration information, and acquiring a key value pair according to the configuration information and the preset key; reading the key-value pair into a cache; and reading the key value pair from the cache, determining a data reading format according to the key value pair, and reading target data from the file to be read according to the data reading format. The invention also provides a data acquisition device, electronic equipment and a storage medium. The invention can improve the reading efficiency of the file and has higher utilization rate of system resources.

摘要：【中文】本发明公开了一种基于人工智能的古诗词生成方法、装置、设备及存储介质，所述方法包括：获取古诗词生成请求中包含的关键词，根据关键词，确定生成古诗词的目标类型，将关键词输入到预设的Transformer模型中，并依据目标类型，生成诗词初稿，再使用预训练的语言模型进行遮挡训练，得到临时诗词初稿，将临时诗词初稿中的每个预测文字与对应的遮挡文字对比，若存在预测文字与遮挡文字不同，则继续对临时诗词初稿进行迭代遮挡预测，直到每个预测文字与对应的遮挡文字均相同，将得到的临时诗词初稿作为目标诗词。通过循环迭代地方式和预训练的语言模型，依次对临时诗词初稿中每个文字进行遮挡预测，实现每个文字根据整体语境不断更新，提高了生成古诗词的质量。 【EN】The invention discloses an artificial intelligence based ancient poetry generating method, an artificial intelligence based ancient poetry generating device, artificial intelligence based ancient poetry generating equipment and a storage medium, wherein the method comprises the following steps: obtaining keywords contained in an ancient poetry generation request, determining a target type for generating the ancient poetry according to the keywords, inputting the keywords into a preset transform model, generating a poetry initial draft according to the target type, then performing shielding training by using a pre-trained language model to obtain a temporary poetry initial draft, comparing each predicted character in the temporary poetry initial draft with a corresponding shielded character, if the predicted character is different from the shielded character, continuing performing iterative shielding prediction on the temporary poetry initial draft until each predicted character is the same as the corresponding shielded character, and taking the obtained temporary poetry initial draft as a target poetry. And sequentially carrying out shielding prediction on each character in the temporary poetry initial draft by a loop iteration mode and a pre-trained language model, realizing continuous updating of each character according to the whole context, and improving the quality of generating the ancient poetry.

摘要：【中文】本申请实施例属于人工智能技术领域，涉及一种数据隔离方法。本申请实施例通过对不同的用户群体进行划分数据库，一个用户群对应一个数据分库并对每个数据分库配置数据源，设置数据源管理器以分配相应的数据源给用户与对应的数据分库连接。所述数据源管理器中存储有其对对应的数据分库的用户信息，将用户群及其所有用户与所述数据源关联映射，当用户访问数据库时，只能通过其对应数据源访问到相应的数据分库，单一访问数据库，从而提高数据安全。另外，通过单一访问的方式，不用轮询所有数据分库，数据访问效率高。本申请还提供一种数据隔离装置、计算机设备及存储介质。本申请实施例通过单一访问数据库，将数据隔离，以保证数据安全。 【EN】The embodiment of the application belongs to the technical field of artificial intelligence and relates to a data isolation method. According to the embodiment of the application, different user groups are divided into the databases, one user group corresponds to one data sub-database, a data source is configured for each data sub-database, and the data source manager is arranged to distribute the corresponding data source to the users to be connected with the corresponding data sub-databases. The data source manager stores user information of the corresponding data sub-databases, associates and maps a user group and all users thereof with the data source, and when a user accesses the database, the user can only access the corresponding data sub-databases through the corresponding data source and only access the database, thereby improving data security. In addition, through a single access mode, all the data sub-databases do not need to be polled, and the data access efficiency is high. The application also provides a data isolation device, computer equipment and a storage medium. According to the embodiment of the application, the data is isolated through single access of the database, so that the data security is guaranteed.

摘要：【中文】本发明涉及人工智能技术领域，提供了一种基于深度学习的白术检测方法、及其相关设备，所述基于深度学习的白术检测方法包括：从图像库中获取待识别的中草药植株图像；将所述中草药植株图像的图像分辨率与预设分辨率进行比较，得到比较结果；根据所述比较结果确定目标植株图像；将所述目标植株图像导入到预先训练好的目标模型中进行识别，确认所述目标植株图像是否包含白术；若包含白术，则将所述识别结果发送给目标用户进行清除处理。本发明的技术方案实现自动识别白术，避免人工干预，从而提高白术识别的准确性以及用户的工作效率。 【EN】The invention relates to the technical field of artificial intelligence, and provides a bighead atractylodes rhizome detection method based on deep learning and related equipment thereof, wherein the bighead atractylodes rhizome detection method based on deep learning comprises the following steps: acquiring an image of the Chinese herbal medicine plant to be identified from an image library; comparing the image resolution of the Chinese herbal medicine plant image with a preset resolution to obtain a comparison result; determining a target plant image according to the comparison result; importing the target plant image into a pre-trained target model for recognition, and determining whether the target plant image contains the bighead atractylodes rhizome; and if so, sending the identification result to a target user for clearing. According to the technical scheme, the automatic identification of the bighead atractylodes rhizome is realized, and manual intervention is avoided, so that the accuracy of the identification of the bighead atractylodes rhizome and the working efficiency of a user are improved.

摘要：【中文】本发明提供一种异常检测方法、电子设备及存储介质。该方法能够当接收到异常检测指令时，获取待检测样本，并确定所述待检测样本是否具有周期性，当所述待检测样本具有周期性时，确定待检测时间点，由于并非对所有数据进行检测，提高了检测效率，从所述待检测样本中确定所述待检测时间点对应的采集值，并调取预先训练的异常检测模型，从所述异常检测模型中获取所述采集值对应的期望值，计算所述采集值与所述期望值之间的残差值，进一步基于所述异常检测模型及所述残差值，确定所述待检测样本是否异常，实现智能运维，由于所述异常检测模型是基于S‑H‑ESD建立的多模型，因此使异常检测具有高精度的特性，进而实现对多种异常的自动化检测。 【EN】The invention provides an abnormality detection method, an electronic device, and a storage medium. The method can obtain a sample to be detected when an abnormity detection instruction is received, determine whether the sample to be detected has periodicity, determine a time point to be detected when the sample to be detected has periodicity, improve detection efficiency because not all data are detected, determine a collection value corresponding to the time point to be detected from the sample to be detected, call a pre-trained abnormity detection model, obtain an expected value corresponding to the collection value from the abnormity detection model, calculate a residual error value between the collection value and the expected value, further determine whether the sample to be detected is abnormal based on the abnormity detection model and the residual error value, realize intelligent operation and maintenance, and enable abnormity detection to have high-precision characteristics because the abnormity detection model is a multi-model established based on S-H-ESD, and further, automatic detection of various abnormalities is realized.

摘要：【中文】一种图像模型检测方法，所述方法包括：获取原始图像样本；将所述原始图像样本输入训练好的主流图像分类模型；使用所述主流图像分类模型，基于动量的梯度迭代算法，对所述原始图像样本进行对抗攻击，获得对抗图像；获取待检测图像模型对所述原始图像样本进行识别后获得的第一识别结果，以及获取所述待检测图像模型对所述对抗图像进行识别后获得的第二识别结果；判断所述第一识别结果与所述第二识别结果是否一致；若所述第一识别结果与所述第二识别结果一致，确定所述待检测图像模型针对所述对抗图像的识别成功。本发明还提供一种图像模型检测装置、电子设备及存储介质。本发明能对深度神经网络模型的安全性进行检测。 【EN】A method of image model detection, the method comprising: obtaining an original image sample; inputting the original image sample into a trained mainstream image classification model; using the mainstream image classification model and a gradient iterative algorithm based on momentum to carry out counterattack on the original image sample to obtain a counterimage; acquiring a first identification result obtained after the original image sample is identified by the image model to be detected, and acquiring a second identification result obtained after the countermeasure image is identified by the image model to be detected; judging whether the first recognition result is consistent with the second recognition result; and if the first recognition result is consistent with the second recognition result, determining that the image model to be detected successfully recognizes the confrontation image. The invention also provides an image model detection device, electronic equipment and a storage medium. The invention can detect the safety of the deep neural network model.

摘要：【中文】本申请实施例公开了一种查询语句边界问题的检测方法、装置、设备及存储介质，涉及数据库语句检测技术领域。该方法包括：接收包含指定的文件存储路径sql边界检测指令；筛选出文件存储路径下的所有sql文件；提取sql文件中的所有sql语句，从sql语句中提取出包含in操作符的sql条件语句；检测sql条件语句中每个in操作符对应的参数数量，判断是否存在所述参数数量大于边界阈值的边界问题；生成用于提示边界问题的推送内容发送至目标用户。所述方法通过合理的步骤对sql文件的内容进行针对性分析，判断出sql文件中的sql语句是否存在因in操作符引起的边界问题，从而方便开发人员了解sql文件中的边界问题并对问题进行定位，提高了开发的质量和对边界问题的处理时效。 【EN】The embodiment of the application discloses a method, a device, equipment and a storage medium for detecting a query statement boundary problem, and relates to the technical field of database statement detection. The method comprises the following steps: receiving a boundary detection instruction containing a specified file storage path sql; screening out all sql files under the file storage path; extracting all sql sentences in the sql file, and extracting sql conditional sentences containing in operators from the sql sentences; detecting the number of parameters corresponding to each in operator in the sql conditional statement, and judging whether a boundary problem that the number of the parameters is larger than a boundary threshold exists or not; and generating push content for prompting the boundary problem and sending the push content to the target user. The method performs targeted analysis on the content of the sql file through reasonable steps, and judges whether the boundary problem caused by the in operator exists in the sql statement in the sql file, so that developers can conveniently know the boundary problem in the sql file and position the problem, and the development quality and the processing timeliness of the boundary problem are improved.

摘要：【中文】本发明涉及人工智能技术，揭露了一种身份识别方法，包括：收集声纹样本集，建立声纹库；对所述声纹样本集进行预处理操作，得到文本相关声纹向量序列集和文本无关声纹向量序列集；将所述文本相关声纹向量序列集进行压缩处理，得到声纹码本集，基于在文本相关声纹识别场景中接收用户的声纹语音内容接收用户的声纹语音内容，根据所述声纹语音内容与声纹码本集的欧式距离识别出所述用户的身份；对所述文本无关声纹向量序列集提取梅尔频率倒谱系数，基于在文本无关声纹识别场景中接收用户的声纹语音内容，根据所述梅尔频率倒谱系数检测出所述用户的身份。本发明还提出一种身份识别装置以及一种计算机可读存储介质。本发明实现了身份的精准识别。 【EN】The invention relates to an artificial intelligence technology, and discloses an identity identification method, which comprises the following steps: collecting a voiceprint sample set and establishing a voiceprint library; preprocessing the voiceprint sample set to obtain a text-related voiceprint vector sequence set and a text-unrelated voiceprint vector sequence set; compressing the text-related voiceprint vector sequence set to obtain a voiceprint codebook set, receiving the voiceprint voice content of a user based on the voiceprint voice content of the user received in a text-related voiceprint recognition scene, and recognizing the identity of the user according to the Euclidean distance between the voiceprint voice content and the voiceprint codebook set; and extracting a Mel frequency cepstrum coefficient from the text-independent voiceprint vector sequence set, receiving voiceprint voice content of a user in a text-independent voiceprint recognition scene, and detecting the identity of the user according to the Mel frequency cepstrum coefficient. The invention also provides an identity recognition device and a computer readable storage medium. The invention realizes accurate identification of the identity.

摘要：【中文】本申请公开了一种业务告警方法、设备及存储介质，其中方法包括：对多条告警记录进行聚类得到多条告警记录中的每条告警记录所属的告警集合；根据多条告警记录和多条告警记录的每条告警记录的业务标签，生成得到训练样本；利用训练样本对支持向量机进行训练，得到业务告警模型；利用业务告警模型对目标告警记录进行分析得到目标告警记录的业务标签，并生成包括目标告警记录和目标告警记录的业务标签的告警信息。本申请先通过聚类来得到包含告警记录和告警记录的业务标签的训练样本，然后利用该训练样本训练支持向量机得到业务告警模型，最后利用业务告警模型分析目标告警记录的业务标签，并生成告警信息，从而实现对异常业务的快速告警。 【EN】The application discloses a service alarm method, equipment and a storage medium, wherein the method comprises the following steps: clustering the plurality of alarm records to obtain an alarm set to which each alarm record in the plurality of alarm records belongs; generating a training sample according to the plurality of alarm records and the service label of each alarm record of the plurality of alarm records; training the support vector machine by using the training sample to obtain a service alarm model; and analyzing the target alarm record by using the service alarm model to obtain a service label of the target alarm record, and generating alarm information comprising the target alarm record and the service label of the target alarm record. The method comprises the steps of firstly obtaining a training sample containing the alarm records and the service labels of the alarm records through clustering, then utilizing the training sample to train a support vector machine to obtain a service alarm model, finally utilizing the service alarm model to analyze the service labels of the target alarm records and generate alarm information, thereby realizing the rapid alarm of abnormal services.