Personalized News Josh Alspector, Alek Kolcz - University of Colorado at Colorado Springs

NewSense User reads news normally Adaptive user model Headline words, keywords –natural language processing Suggests articles to read Reconfigure web pages Extend to all interesting information

Data Analysis “Bag of words” for visited headlines –stemming, stop words Score recent words higher Similarity measure –cosine (query, document) word vectors “Query” based on visited documents –terms in relevant (visited) - factor*terms in irrelevant (not visited) documents

Evaluation of Data Precision: well-defined –visited&relevant/all visited Recall: ill-defined here –visited&relevant/all&relevant Use avg. precision –weighted by threshold of relevancy Rocchio and Bayes are best: P=0.75

Universal Content Advisor Model for other intuitive systems –shopping advisor –personal information broker –space flight system advisor Personal preference models –key to agent-based systems –information filters –targeted advertising

Intuitive Technology Ubiquitous – all users have tools and networks Invisible –helpful, not obtrusive Inexpensive and widely available Smart, adapt to user Intuitive, not just user-friendly

Conclusion Personal advisor Unobtrusive and intuitive Help to user Useful to advertiser Makes content as well as sales both useful and personal Applicable to all information sources