With the ever increasing size of the web, relevant information extraction on the Internet with
a query formed by a few keywords has become a big challenge. Query Expansion (QE) …

For thousands of years people have realized the importance of archiving and finding
information. With the advent of computers, it became possible to store large amounts of …

The goal of text ranking is to generate an ordered list of texts retrieved from a corpus in
response to a query. Although the most common formulation of text ranking is search …

The extraction of useful insights from text with various types of statistical algorithms is
referred to as text mining, text analytics, or machine learning from text. The choice of …

Abstract The Probabilistic Relevance Framework (PRF) is a formal framework for document
retrieval, grounded in work done in the 1970–1980s, which led to the development of one of …

Locating timely, useful information during crises and mass emergencies is critical for those
forced to make potentially life-altering decisions. As the use of Twitter to broadcast useful …

As recently as the 1990s, studies showed that most people preferred getting information
from other people rather than from information retrieval systems. Of course, in that time …

The experimental evidence accumulated over the past 20 years indicates that text indexing
systems based on the assignment of appropriately weighted single terms produce retrieval …

Information retrieval (IR) has changed considerably in recent years with the expansion of the
World Wide Web and the advent of modern and inexpensive graphical user interfaces and …

At ACM SIGIR'94, I compared the effectiveness of uncertainty sampling with that of random
sampling and relevance sampling in choosing training data for a text categorization data set …