Method, device, computing device and medium for discovering poi transition events
A technology for discovering methods and events, applied in computing, instruments, electrical and digital data processing, etc., can solve the problems of time-consuming and labor-intensive, low judgment accuracy, low recall rate, etc., to improve recall rate, ensure accuracy, solve problems Judging less accurate effects
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Embodiment 1
[0026] figure 1 It is a flow chart of the method for discovering POI transition events provided by Embodiment 1 of the present invention. This embodiment is applicable to the situation where the information describing POI transition events is confirmed through mining massive network information. The method can be executed by a POI change event discovery device, which can be implemented in software and / or hardware, and can be integrated on any computing device, including but not limited to a server.
[0027] Such as figure 1 As shown, the POI transition event discovery method provided in this embodiment may include:
[0028] S110. Determine a first sentence vector of the training sentence in the training text based on the correlation between each word in the training sentence.
[0029] 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 information text...
Embodiment 2
[0047] figure 2 It is a flow chart of the method for discovering POI transition events 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:
[0048] S210. Segment the training sentence, 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 in the training text.
[0049] In this embodiment, the vector representation of each word obtained by segmenting the training sentence is composed of three parts of vectors: word embeddings (Word Embeddings), position vectors (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...
Embodiment 3
[0062] Figure 4 It is a schematic structural diagram of a POI transition event discovery device provided in Embodiment 3 of the present invention. This embodiment is applicable to the situation where the information describing POI transition events is confirmed 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.
[0063] Such as Figure 4 As shown, the POI transition event discovery 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:
[0064]The first vector determination module 310 is used to determine the first sentence vector of the training sentence in the training text based on the relevance between each word in the training sentence;
[0065] The second vector determination module 320 is used to determine the...
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