Recommendation on Commercial Intention in Dialogs
Date Issued
2007
Date
2007
Author(s)
Huang, Hung-Chi
DOI
en-US
Abstract
Instant messaging applications are the most popular applications on Internet. Users can communicate with each other by inputting texts or symbols in natural languages. While the conversation is in progress, some irrelevant advertisement links would appear randomly. Our target is to establish a dialog analysis system in which meaningful advertisement links highly relevant to the dialog contents can therefore be proposed, and thereafter the click rate of the ad links can be increased.
The proposed model uses Yahoo! Directory tree as the data-comparison source, and classifies each dialog into one of the 14 categories of Yahoo! Directory, such as Recreation & Sports, Art, Science, etc. The system will calculate the weight by terms from the dialogs according to their document frequency in Yahoo! Directory tree. Also a TFIDF-similar is considered and evaluated by computing the term frequency in dialogs and each category.
For bettering the data resource, we develop an expansion algorithm to expand the original Yahoo! Directory tree with its accompanying HTML files, in which some related web pages with titles, links, and snippets are saved. The experiment results show that expansion is meaningful with better performance. For convenience, we call the data sources as corpora.
In the best setting of system parameters in the model, we conclude using Noun and Expansion Corpus can get the best result, which brings a 90% of F-value. This can give us confidence that we can correctly guess the commercial intentions of 90 dialogs from a given set of 100 dialogs.
Besides, a special statistic, hit speed, is proposed to evaluate when our system can correctly retrieve the correct commercial category and provide relevant ad links. So far we are confident to do so in the middle round of a given conversation. We also define a decision tree which can decide new terms from dialogs and retrieve its definitions. After some refinement, we can get interesting geographical transliteration terms and people names.
Finally we provide some detailed results and conclude our models to implement an effective commercial recommendation system on IM applications, and discuss some interesting topics for future research.
Subjects
即時通訊
對話分析
廣告意圖
廣告推薦
語料擴增
線上目錄
Instant messaging
dialog analysis
commercial intention
advertisement suggestion
corpus expansion
on-line directory
Type
thesis
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