A Gesture Query Intent Prediction Method Based on Hidden Markov Model

Abstract

The present invention relates to a gesture query intention prediction method based on a hidden Markov model, starting from the user gesture interaction process, analyzing gesture categories and their corresponding feature attributes commonly used in gesture search, and then constructing gesture query based on hidden Markov characteristics Intent model, on this basis, the parameters of gesture query intent model are calculated by using gesture interaction features, and the optimal query intent corresponding to gesture interaction events is predicted by using Viterbi theory. Based on the characteristic that the gesture interaction process conforms to the Hidden Markov Process, the present invention captures the user's query intention by using the gesture operation feature, and provides certain guidance for the user gesture interaction process. The present invention can be applied to gesture interaction-oriented exploratory search scenarios, enabling users to obtain information that meets their intentions during the gesture interaction process, and improving the fluency and satisfaction of gesture interaction.

Description

technical field [0001] The invention relates to a gesture query intention prediction method based on a hidden Markov model, and belongs to the technical fields of human-computer interaction and information retrieval. Background technique [0002] With the rapid development of touch interaction technology, according to statistics, by 2017, 87% of the world's intelligent networked devices are tablets and smartphones, and the share of PCs is less than 13%, which shows that multi-touch interactive devices will become the most important part of human-computer interaction. Gesture interaction has gradually become one of the leading ways of human-computer interaction. Therefore, the user uses gestures such as sliding up, sliding down, zooming in, zooming out, and clicking to search for information during the information search process. In order to deepen the understanding of the searched content, the user repeatedly performs the above gestures and iteratively tries and errors. Howe...

AI Technical Summary

Problems solved by technology

This prediction method analyzes the user's click behavior on the search results corresponding to the original search statement based on the log information of the user's interaction with the search engine. It mainly considers the common click behavior and does not consider the application requirements of gesture interaction.

In another invention patent "Touch to Search" (Application No.: 201380072159.8, Authorization No.: CN 104969164 A), the user can select the content displayed on the touch screen by using gestures instead of typing a search query into the search interface, based on gesture data Identify a subset of content to select a set of candidate search queries, and calculate the likelihood score for each candidate search query, and finally select one or more candidate search queries. Although this invention makes full use of gesture data, it does not use gesture data Combined with user query intent

[0005] In summary, most methods do not focus on the relationship between gesture operation features and user query intentions, and extract information that meets user intentions.

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