Method for identifying financial advertisements in text advertisements
An advertising and financial technology, applied in the field of advertising recognition, can solve the problem that the advertising analysis model cannot effectively identify financial advertisements, and achieve the effects of preventing over-fitting, improving accuracy, and good classification effects
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Embodiment 1
[0022] Embodiment 1: as figure 1 As shown, it is a logical schematic diagram of the overall functional structure of this embodiment. The method for identifying financial advertisements in text advertisements disclosed in this embodiment includes the following steps:
[0023] (1) Acquire crawled advertisement text data from the database; advertisement text data mainly comes from sites such as search engines, Baidu Tieba, financial portals, and news portals.
[0024] (2) Preprocess the text data, perform word segmentation and remove useless information, so that the text can better represent semantic information. Data preprocessing mainly includes the following steps:
[0025] i. Word segmentation: In Chinese, a word is the smallest unit that constitutes a language and has semantics. A word cannot better represent the semantic information it carries. Therefore, it is necessary to convert the text data without intervals into continuous phrases;
[0026] ii. Removing stop words:...
Embodiment 2
[0041] The present embodiment takes the identification of financial advertisements in the text advertisements in the Baidu search engine as an example to describe the technical scheme and steps. A method for identifying financial advertisements in the text advertisements in the Baidu search engine includes the following steps:
[0042] Step 1: Obtain 1,000 advertising texts from the database that have already been crawled from the Baidu search engine, where the ratio of the training set to the test set is 3:1;
[0043] Step 2: Segment the text content of the training set through the jieba word segmentation tool:
[0044] jiaba word segmentation tool: It is a python package for natural language processing, which can be downloaded and used directly through pip.
[0045] Step 3: Filter the phrases obtained after word segmentation in step 2 through the stop vocabulary list released by HIT Natural Language Processing Laboratory, and remove the words in the stop vocabulary list. The...
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