4,659 research outputs found
BCP3: Summary of Theory
I discuss a number of the highlights in theory presented at the BCP3
conference. These included new, and more stringent, CKM fits; a critical
overview of heavy hadron lifetimes; progress in computing rates and
CP-asymmetries in charmless B-decays; a thorough discussion of the implications
of the new results on ; and, finally, a peek at the
future, trying to estimate how well one is going to be able to measure the
unitarity triangle angles.Comment: To appear in the Proceedings of the Third International Conference on
B Physics and CP Violation, Taipei, Taiwan, December 3-7, 199
Social Collaborative Retrieval
Socially-based recommendation systems have recently attracted significant
interest, and a number of studies have shown that social information can
dramatically improve a system's predictions of user interests. Meanwhile, there
are now many potential applications that involve aspects of both recommendation
and information retrieval, and the task of collaborative retrieval---a
combination of these two traditional problems---has recently been introduced.
Successful collaborative retrieval requires overcoming severe data sparsity,
making additional sources of information, such as social graphs, particularly
valuable. In this paper we propose a new model for collaborative retrieval, and
show that our algorithm outperforms current state-of-the-art approaches by
incorporating information from social networks. We also provide empirical
analyses of the ways in which cultural interests propagate along a social graph
using a real-world music dataset.Comment: 10 page
From Frequency to Meaning: Vector Space Models of Semantics
Computers understand very little of the meaning of human language. This
profoundly limits our ability to give instructions to computers, the ability of
computers to explain their actions to us, and the ability of computers to
analyse and process text. Vector space models (VSMs) of semantics are beginning
to address these limits. This paper surveys the use of VSMs for semantic
processing of text. We organize the literature on VSMs according to the
structure of the matrix in a VSM. There are currently three broad classes of
VSMs, based on term-document, word-context, and pair-pattern matrices, yielding
three classes of applications. We survey a broad range of applications in these
three categories and we take a detailed look at a specific open source project
in each category. Our goal in this survey is to show the breadth of
applications of VSMs for semantics, to provide a new perspective on VSMs for
those who are already familiar with the area, and to provide pointers into the
literature for those who are less familiar with the field
Reducing the number of inputs in nonlocal games
In this work we show how a vector-valued version of Schechtman's empirical
method can be used to reduce the number of inputs in a nonlocal game while
preserving the quotient of the quantum over the classical
bias. We apply our method to the Khot-Vishnoi game, with exponentially many
questions per player, to produce another game with polynomially many () questions so that the quantum over the classical bias is
- …