3 results about "Author name" patented technology

The application provides a code statistics method and device, electronic equipment and storage medium, the method comprises: obtaining project information of a plurality of projects under a plurality of hierarchical groups to be counted; filtering out effective branches through the project information and a preset branch list, and extracting a plurality of code submission records carrying submission hash values from the effective branches; using the submission hash values to deduplicate the plurality of code submission records, filtering out effective code submission records in the deduplicated code submission records, and identifying author names to obtain garbled author names and normal author names; grouping the effective code submission records by email addresses, repairing garbled author names in the groups by using normal author names in the groups. Identify the main author and non-main author names in the group; add the code modification information of the non-main author names in each group to the main author names, and obtain the code statistics contribution of the main author names corresponding to each group, so as to improve the accuracy of code statistics.

This invention provides a method, application, and electronic device for constructing an author name disambiguation model. First, a name block and an initial training set consisting of entity pair training samples are constructed. An author name disambiguation baseline model is trained based on the initial training set. The baseline model is then used to calculate the global feature importance vector for each entity pair training sample through feature attribution calculation. The score for each entity pair training sample is calculated based on the global feature importance vector and a non-empty indicator vector, and a training set is selected. The baseline model is then retrained using the selected training set to obtain the author name disambiguation model. The objective loss function of the author name disambiguation model includes classification loss and attribution prior regularization, improving model interpretability, reducing information loss due to metadata sparsity, suppressing model attention drift, and being compatible with various model structures. It has low engineering modification costs and can be widely applied to name disambiguation scenarios in various academic data processing systems.

The invention discloses an author name disambiguation method and system, and belongs to the technical field of natural language processing. The method comprises the following steps: acquiring and preprocessing a paper data set; blocking processing according to name fingerprints; performing first-stage merging based on same mechanism and text similarity; second-stage cross-mechanism judgment is carried out based on bidirectional partner coverage, time cross constraint and mechanism transfer prior; executing constrained graph clustering; according to the method, the disambiguation accuracy and recall rate of the authors with the same name can be improved under the condition that only abstracts and metadata exist, the situation that the authors replace work units can be further accurately recognized, and the method is suitable for scenes such as academic literature retrieval and researchers evaluation.