Topic-specific scoring of documents for relevant retrieval
There has been mixed success in applying semantic component analysis (LSA, PLSA, discrete PCA, etc.) to information retrieval. Here we combine topic-specific link analysis with discrete PCA (a semantic component method) to develop a topic relevancy score for information retrieval that is used in post-filtering documents retrieved via regular Tf.Idf methods. When combined with a novel and intuitive “topic by example” interface, this allows a user-friendly manner to include topic relevance into search. To evaluate the resultant topic and link based scoring, a demonstration has been built using the Wikipedia, the public domain encyclopedia on the web.