17,684 research outputs found
Sentence alignment in DPC: maximizing precision, minimizing human effort
A wide spectrum of multilingual applications have aligned parallel corpora as their prerequisite. The aim of the project described in this paper is to build a multilingual corpus where all sentences are aligned at very high precision with a minimal human effort involved. The experiments on a combination of sentence aligners with different underlying algorithms described in this paper showed that by verifying only those links which were not recognized by at least two aligners, an error rate can be reduced by 93.76% as compared to the performance of the best aligner. Such manual involvement concerned only a small portion of all data (6%). This significantly reduces a load of manual work necessary to achieve nearly 100% accuracy of alignment
Electromagnetic Probes
A review is presented of dilepton and real photon measurements in
relativistic heavy ion collisions over a very broad energy range from the low
energies of the BEVALAC up to the highest energies available at RHIC. The
dileptons cover the invariant mass range \mll = 0 - 2.5 GeV/c, i.e. the
continuum at low and intermediate masses and the light vector mesons, . The review includes also measurements of the light vector mesons
in elementary reactions.Comment: To be published in Landolt-Boernstein Volume 1-23A; 40 pages, 24
figures. Final version updated with small changes to the text, updated
references and updated figure
Filling Knowledge Gaps in a Broad-Coverage Machine Translation System
Knowledge-based machine translation (KBMT) techniques yield high quality in
domains with detailed semantic models, limited vocabulary, and controlled input
grammar. Scaling up along these dimensions means acquiring large knowledge
resources. It also means behaving reasonably when definitive knowledge is not
yet available. This paper describes how we can fill various KBMT knowledge
gaps, often using robust statistical techniques. We describe quantitative and
qualitative results from JAPANGLOSS, a broad-coverage Japanese-English MT
system.Comment: 7 pages, Compressed and uuencoded postscript. To appear: IJCAI-9
Multilingual domain modeling in Twenty-One: automatic creation of a bi-directional translation lexicon from a parallel corpus
Within the project Twenty-One, which aims at the effective dissemination of information on ecology and sustainable development, a sytem is developed that supports cross-language information retrieval in any of the four languages Dutch, English, French and German. Knowledge of this application domain is needed to enhance existing translation resources for the purpose of lexical disambiguation. This paper describes an algorithm for the automated acquisition of a translation lexicon from a parallel corpus. New about the presented algorithm is the statistical language model used. Because the algorithm is based on a symmetric translation model it becomes possible to identify one-to-many and many-to-one relations between words of a language pair. We claim that the presented method has two advantages over algorithms that have been published before. Firstly, because the translation model is more powerful, the resulting bilingual lexicon will be more accurate. Secondly, the resulting bilingual lexicon can be used to translate in both directions between a language pair. Different versions of the algorithm were evaluated on the Dutch and English version of the Agenda 21 corpus, which is a UN document on the application domain of sustainable development
Coalitions and Cliques in the School Choice Problem
The school choice mechanism design problem focuses on assignment mechanisms
matching students to public schools in a given school district. The well-known
Gale Shapley Student Optimal Stable Matching Mechanism (SOSM) is the most
efficient stable mechanism proposed so far as a solution to this problem.
However its inefficiency is well-documented, and recently the Efficiency
Adjusted Deferred Acceptance Mechanism (EADAM) was proposed as a remedy for
this weakness. In this note we describe two related adjustments to SOSM with
the intention to address the same inefficiency issue. In one we create possibly
artificial coalitions among students where some students modify their
preference profiles in order to improve the outcome for some other students.
Our second approach involves trading cliques among students where those
involved improve their assignments by waiving some of their priorities. The
coalition method yields the EADAM outcome among other Pareto dominations of the
SOSM outcome, while the clique method yields all possible Pareto optimal Pareto
dominations of SOSM. The clique method furthermore incorporates a natural
solution to the problem of breaking possible ties within preference and
priority profiles. We discuss the practical implications and limitations of our
approach in the final section of the article
Pedestrian Trajectory Prediction with Structured Memory Hierarchies
This paper presents a novel framework for human trajectory prediction based
on multimodal data (video and radar). Motivated by recent neuroscience
discoveries, we propose incorporating a structured memory component in the
human trajectory prediction pipeline to capture historical information to
improve performance. We introduce structured LSTM cells for modelling the
memory content hierarchically, preserving the spatiotemporal structure of the
information and enabling us to capture both short-term and long-term context.
We demonstrate how this architecture can be extended to integrate salient
information from multiple modalities to automatically store and retrieve
important information for decision making without any supervision. We evaluate
the effectiveness of the proposed models on a novel multimodal dataset that we
introduce, consisting of 40,000 pedestrian trajectories, acquired jointly from
a radar system and a CCTV camera system installed in a public place. The
performance is also evaluated on the publicly available New York Grand Central
pedestrian database. In both settings, the proposed models demonstrate their
capability to better anticipate future pedestrian motion compared to existing
state of the art.Comment: To appear in ECML-PKDD 201
- ā¦