Research And Application On Promoting Keywords On Online Trading Platform

In E-commerce market, it is important to choose correct word if oneneeds to advertise his product in the webpage otherwise it is very easy toget lost in the huge platform. Every word of the sentence provides certainposition in the search engine page. So for this it is necessary to know thecommon keywords that the competitors are buying to get visible andplacement in the webpage.In this paper, we present a novel approach to this problem bysuggesting the new word on ecommerce platform based on concepthierarchy by building hierarchical dictionary in tree structure. Given a titleof the product that advertisers want to sell in the platform, we first parse itinto separate words by Forward and Backward Maximum MatchingAlgorithm and generate the bid words according to the each parsed wordsof the title. We generate new words from title split and eventually expandthe query of suggested words by matching with the most keywords in thedictionary and suggest new keyword according to the relation score. Ithelps them not only raise their placement in the platform and get visibleamong buyers but also make them competent among the retailers sellingthe similar product in the platform.We will show the effectiveness of our proposed method byexperimental result and prove that our system successfully covers accuracyrequirements by suggesting most relevant keyword. We have used Java toimplement our algorithm and at the end we sort the keywords produced byour algorithm with those provided by the keyword bidding service systemof Taobao.