Research Of Smart Tourism Explanation Knowledge Extraction Method

With the development of transportation capacity,the scope of people's activities is gradually expanding,and the number of tourists is increasing.In this regard,the National Tourism Administration issued a series of policies in the hope that the tourism industry can integrate into the current hot AI related content,which is also vigorously developed by the country,so as to improve the quality of the tourism industry.As the current research hotspot,artificial intelligence is rapidly integrating with various industries to improve and optimize the original services.It has been widely used in medical health,smart home,e-commerce customer service and other fields,but the research and application in tourism explanation are still few.Therefore,the integration application of artificial intelligence and tourism industry has great development potential.With the rapid development of Internet technology,all users can publish content on the Internet,resulting in a sharp increase in the amount of information.The main problem of knowledge base construction has changed from no target content to how to extract and organize the target content.So it is a key problem to extract and organize the expected content from the mass information.Because of the poor expansibility and low efficiency of manual information extraction,it can't meet the needs of extracting effective information from massive information,so it needs the high computing performance of computer to complete the knowledge extraction work.Knowledge extraction is the synthesis of many basic natural language processing technologies,which can extract effective information from massive information and organize it to form knowledge.There are already some tourism explanation systems in the market,such as chain view travel and Sanmao travel.However,the construction process of knowledge base behind their explanation mainly adopts manual method.The tourism explanation system relying on manual method to extract knowledge to build explanation knowledge base has the problem of difficulty in scenic spot expansion.In order to solve this problem,this paper studies a knowledge extraction method based on multi model fusion,and designs a set of intelligent explanation system for tourist attractions.The specific work is as follows:Firstly,design a reasonable data acquisition scheme.The data source selection and data characteristics are analyzed,and then a reasonable data acquisition and storage scheme is designed to support the subsequent model training data.After analyzing the requirements of subsequent models,it is clear that the data preprocessing process needs to do named entity recognition,associated entity pair extraction and noun phrase extraction,so as to speed up the model training process and improve the efficiency of knowledge extraction.The storage scheme of associated entity pairs and noun phrases is designed.Secondly,a knowledge extraction method based on multi model fusion is proposed.The process of knowledge extraction is divided into two key steps: entity relation extraction and attribute extraction.In the process of entity relation extraction,the improved k-means method is used.A method based on sample density and weight is used to find the number and center of clusters,and then K-means clustering is used.It can not only make the effect of extracting relation words better,but also speed up the clustering speed.Attribute extraction is divided into two parts,one part is based on lda2 vec model to cut text to obtain knowledge elements,and then do clustering analysis on knowledge elements to obtain knowledge elements;the other part first extracts noun phrases in the text,and then does clustering analysis on the feature vector of noun phrases based on hierarchical clustering improved k-means method to extract attributes.Thirdly,a set of intelligent explanation system is designed and developed.The overall architecture of the system is designed,the system development environment is introduced,and the evaluation index of the system is determined.The whole tourism intelligent explanation system is divided into three small systems: data collection,knowledge extraction and task dialogue.The data acquisition system is mainly responsible for data acquisition,preprocessing and storage,and provides data support for the training of knowledge extraction model.The knowledge extraction system is mainly responsible for the text data obtained by the data acquisition system,and constructs the explanation knowledge base through the knowledge extraction model.The task-based dialogue system mainly obtains the user's demand information,and then extracts the corresponding content in the explanation knowledge base to feed back to the user.Finally,the application test in the simulation environment verifies the accuracy and real-time performance of the system in the scene with simple knowledge structure,and proves the practical significance of the system to a certain extent.