Internet data clearing method based on single public opinion event
A data clearing and Internet technology, applied in the field of data processing, can solve the problem of large noise in the results of public opinion processing
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Embodiment 1
[0062] The steps of segmenting the single-target public opinion data include: constructing a prefix dictionary based on the statistical dictionary, realizing efficient word map scanning, segmenting the sentences in the single-target public opinion data according to the prefix dictionary, and outputting all the segmentation results, according to The segmentation results generate a directed acyclic graph (DAG) composed of Chinese characters in the single target public opinion data, and use dynamic programming to find the maximum probability path in the directed acyclic graph, find out the maximum segmentation combination based on word frequency, and output Segment sentences into words.
[0063] The step of segmenting the sentences in the single-target public opinion data also includes:
[0064] If there are words not included in the prefix dictionary in the single-target public opinion data, the Viterbi algorithm is used for sentence segmentation based on the HMM model of the wo...
Embodiment 2
[0067] Public opinion incident 2: A public opinion incident of bullying students occurred in a school in a certain area
[0068] Step 1: Publicly collect relevant public opinion big data;
[0069] Step 2: Format public opinion data to generate formatted public opinion data with complete standards such as title, author, release time, content, source, etc.;
[0070] Step 3: Create a public opinion rule system, such as character subject: teacher, student; region: region name; event subject: school name; event: bullying, violent teaching, etc.; set the public opinion weight level as event subject, region, event, and character subject ;
[0071] Step 4: Use the segmentation algorithm to segment and combine public opinion data. Take the title of public opinion data as an example. Data 1: Campus bullying occurred in a certain school in a certain city. Use the segmentation algorithm to output sentences: certain city / some / school / occurrence / campus / bullying; Data 2: Campus bullying in...
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