Inventory page identification method, apparatus, computing device and medium
A recognition method and marking technology, applied in computing, computer parts, character and pattern recognition, etc., to achieve effective screening, improve information recommendation results, and accurate recognition
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Embodiment 1
[0027] figure 1 It is a flowchart of an inventory page identification method provided in Embodiment 1 of the present invention. This embodiment is applicable to the situation of identifying an inventory page by mining massive network information. The method can be executed by an inventory page identification device, which can be implemented in the form of software and / or hardware, and can be integrated on any computing device, including but not limited to a server.
[0028] Such as figure 1 As shown, the inventory page identification method provided in this embodiment may include:
[0029] S110. Determine a first title vector of the training text title based on the correlation between each word in the training text title.
[0030] Before training the model based on deep learning ideas, it is necessary to prepare the training text in advance. The training text can be any social media text, such as various news or information released on platforms such as Weibo, web pages, and...
Embodiment 2
[0043] figure 2 It is a flow chart of the inventory page identification method provided by Embodiment 2 of the present invention, and this embodiment is further optimized on the basis of the foregoing embodiments. Such as figure 2 As shown, the method may include:
[0044] S210. Segment the title of the training text, and use the word vector analysis model to determine the word vector, position vector and part-of-speech vector of each word obtained through word segmentation.
[0045] In this embodiment, the vector representation of each word obtained by segmenting the training text title is composed of three parts of vectors: word embeddings (Word Embeddings), position embeddings (Position Embedding) and part-of-speech vectors (POSEembedding). Among them, the word vector can be obtained by using a pre-trained unsupervised model, such as the word2vector model, etc. The unsupervised model can be obtained based on existing open source word vectors or self-built training corpu...
Embodiment 3
[0057] Figure 4 It is a schematic structural diagram of an inventory page identification device provided in Embodiment 3 of the present invention. This embodiment is applicable to the situation of identifying inventory pages by mining massive network information. The device can be implemented in the form of software and / or hardware, and can be integrated on any computing device, including but not limited to a server.
[0058] Such as Figure 4 As shown, the inventory page identification device provided in this embodiment may include a first vector determination module 310, a second vector determination module 320 and a model training module 330, wherein:
[0059] The first vector determination module 310 is used to determine the first title vector of the training text title based on the correlation between the words in the training text title;
[0060] The second vector determination module 320 is used to determine the second title vector of the training text title by using...
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