In this paper we study the problem of finding most topical named entities among all entities in a document, which we refer to as focused named entity recognition. We show that th...
The next wave in search technology will be driven by the identification, extraction, and exploitation of real-world entities represented in unstructured textual sources. Search sy...
Building a model using machine learning that can classify the sentiment of natural language text often requires an extensive set of labeled training data from the same domain as t...
The classical (ad hoc) document retrieval problem has been traditionally approached through ranking according to heuristically developed functions (such as tf.idf or bm25) or gene...
Unsupervised learning algorithms have been derived for several statistical models of English grammar, but their computational complexity makes applying them to large data sets int...