Micro-blog is a platform for users to get information and convey their own ideas. In recent years, the emotional analysis of micro-blog has gradually become a hot topic. The publication of micro blog not only includes text, but also emoticons are a part that cannot be ignored. Traditional research methods ignore the importance of emoticons to the emotional polarity of text when preprocessing the micro blog. This paper proposes a research method of text emotion analysis based on the fusion of emoticons. By micro-blog to crawl the data preprocessing, selected text in the emoticons, using emotional dictionary gives corresponding weights and calculate the score, then transform text into the corresponding word vector sequence, using Bidirectional Gated Recurrent Unit network context information text emotion tendency, finally selects the Conditional Random Field polarity judgment of text. The experimental results show that the accuracy of the proposed method is up to 89%.
In this paper, we combine quantum computation and clustering algorithm in data mining. In this algorithm, we give the
suppose that around the clustering centers exits a potential field, in Hilbert space, we get the potential energy function
through Schrödinger equation. We use this as rules to assign element to clusters. Finally, through the simulative
experiment, we validated its validity and feasibility while applied in data mining of tourism emergency.
To mine useful tourism events' knowledge from different data sources distributed on Internet, we design a kind of data
mining "Softman" which is based on quantum computing and artificial immune system. The thinking state of softman is
encoded as quantum-bits (qubits). Its advantage is that the qubit linear superposition can represent the probability of
softman taking action according to its thinking state, so it is consistent with the way of human. Then we apply quantuminspired
immune clone algorithm to the thinking state evolution of softman, which utilizes immune learning and clonal
selection to improve softman's learning ability. A multi-softmen organization can be used to do parallel data mining.
And some organizations can also be applied on several data sources to implement distributed data mining.
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