Search is one of the most quickly growing applications in the mobile market. As people rely
more on portable devices for performing search, it becomes increasingly important to …

The recognition of names and their associated categories within unstructured text
traditionally relies on semantic lexicons and gazetteers. The amount of effort required to …

Named entity lists provide important features for language understanding, but typical lists
can contain many ambiguous or incorrect phrases. We present an approach for …

Assume that you are looking for information about a particular person. A search engine
returns many pages for that person's name. Some of these pages may be on other people …

We propose AutoName, an unsupervised framework that extracts a name for a set of query
entities from a large-scale text corpus. Entity-set naming is useful in many tasks related to …

Abstract Named Entity Recognition and Classification (NERC) is an important component of
applications like Opinion Tracking, Information Extraction, or Question Answering. When …

This paper addresses Named Entity Mining (NEM), in which we mine knowledge about
named entities such as movies, games, and books from a huge amount of data. NEM is …

We use search engine results to address a particularly difficult cross-domain language
processing task, the adaptation of named entity recognition (NER) from news text to web …

Assume that we are looking for information about a particular person. A search engine
returns many pages for that person's name. Some of these pages may be on other people …

In this paper we propose a completely unsupervised method for open-domain entity
extraction and clustering over query logs. The underlying hypothesis is that classes defined …