Abstract: Embodiments of the present disclosure disclose a method and apparatus for constructing a quality evaluation model, an electronic device and a computer-readable storage medium. A specific implementation mode of the method comprises: acquiring samples of knowledge contents; extracting statistical features, semantic features, and image features respectively from the samples of knowledge contents; and constructing a quality evaluation model for knowledge according to the statistical features, the semantic features, and the image features. On the basis of the prior art, this implementation mode additionally uses semantic features and image features of knowledge contents to construct a more accurate quality evaluation model based on multi-dimensional features that characterize the actual quality of a knowledge, which may well discover some brief but very useful summary knowledge in an enterprise and may recommend high-quality knowledge more accurately for employees in the enterprise.

Abstract: The present disclosure provides a method of recommending a document, an electronic device, and a storage medium, relating to fields of intelligent recommendation, deep learning etc. The method of recommending a document includes: acquiring a document operated by a user, as a reference document; determining, from a plurality of initial documents, at least one candidate document for the reference document, wherein a document content of each candidate document is associated with a document content of the reference document, based on preset knowledge system data; and recommending a target document in the at least one candidate document to the user, the target document including a document that the user is currently interested in and a document that the user is interested in after a preset time period.

Abstract: An information searching method, an electronic device and a storage medium are provided, which are related to the field of deep learning and the like. The method includes: acquiring K related second-type-entity corresponding to a target first-type-entity from a relational map based on a search word related to the target first-type-entity; wherein K is an integer greater than or equal to 1; selecting M candidate second-type-entity from the K related second-type-entity based on data representing a relation between the K related second-type-entity and the target first-type-entity; wherein M is an integer greater than or equal to 1 and less than or equal to K; selecting N target second-type-entity from the M candidate second-type-entity as a search result; wherein N is an integer greater than or equal to 1 and less than or equal to M.

Abstract: The present disclosure provides an information recommendation method, which relates to a field of knowledge graph. The method includes: acquiring request information; extracting a request entity word representing an entity from the request information; determining recommendation information based on the request entity word and a pre-constructed knowledge graph; and pushing the recommendation information, wherein the knowledge graph is constructed based on a text, and the knowledge graph indicates a first word representing a source of the text. The present disclosure further provides an information recommendation apparatus, an electronic device and a computer-readable storage medium.

Abstract: Embodiments of the present disclosure disclose a method and apparatus for constructing a quality evaluation model, an electronic device and a computer-readable storage medium. A specific implementation mode of the method comprises: acquiring samples of knowledge contents; extracting statistical features, semantic features, and image features respectively from the samples of knowledge contents; and constructing a quality evaluation model for knowledge according to the statistical features, the semantic features, and the image features. On the basis of the prior art, this implementation mode additionally uses semantic features and image features of knowledge contents to construct a more accurate quality evaluation model based on multi-dimensional features that characterize the actual quality of a knowledge, which may well discover some brief but very useful summary knowledge in an enterprise and may recommend high-quality knowledge more accurately for employees in the enterprise.

Abstract: A method for skipping an initialization process of synchronization of an RAID 1 device skips synchronization process of the RAID1 device through a bitmap technique. First, an RAID1 device is established, a space of the same size is divided from each member disk of the RAID1 device for storing a bitmap corresponding to each data block on each member disk. When a read/write operation is executed on the RAID1 device, before the bit value in the bitmap corresponding to the data block is read, whether the bitmap exists or not is determined first, then corresponding operation is executed according to the bit value in the bitmap corresponding to data block requesting the read/write operation. The method skips synchronization process of the RAID 1 device during the initial establishment, thereby largely saving the time required by the synchronization process for initialization, and further improving the overall performance of the RAID1 device.