𝔖 Bobbio Scriptorium
✦   LIBER   ✦

Information extraction and qualitative descriptions from dynamic simulation data

✍ Scribed by S. Chandra

Publisher
Elsevier Science
Year
1998
Tongue
English
Weight
909 KB
Volume
69
Category
Article
ISSN
0045-7949

No coin nor oath required. For personal study only.

✦ Synopsis

A description system developed to provide succinct qualitative descriptions from simulations over a period of time is detailed here. Qualitative attributes are useful in descriptions of analysis, experimental data, real-time monitoring and eventually in control. Fuzzy methods are used to map the quantitative data into qualitative attributes and compress the information. A simple natural language interface is used to query the database. A feature extractor, geometry description interpreter and information compression schema are shown.

📜 SIMILAR VOLUMES

Systematic Extraction of Structure–Activ
Systematic Extraction of Structure–Activity Relationship Information from Biological Screening Data
✍ Mathias Wawer; Jürgen Bajorath 📂 Article 📅 2009 🏛 John Wiley and Sons 🌐 English ⚖ 552 KB

## Abstract __A data mining approach is introduced that automatically extracts SAR information from high‐throughput screening data sets and that helps to select active compounds for chemical exploration and hit‐to‐lead projects. SAR pathways are systematically identified consisting of sequences of

From simulation data to conformational e
From simulation data to conformational ensembles: Structure and dynamics-based methods
✍ Huisinga, Wilhelm; Best, Christoph; Roitzsch, Rainer; Sch�tte, Christof; Cordes, 📂 Article 📅 1999 🏛 John Wiley and Sons 🌐 English ⚖ 369 KB

Statistical methods for analyzing large data sets of molecular configurations within the chemical concept of molecular conformations are described. The strategies are based on dependencies between configurations of a molecular ensemble; the article concentrates on dependencies induced by (a) correla

A semi-supervised active learning algori
A semi-supervised active learning algorithm for information extraction from textual data
✍ Tianhao Wu; William M. Pottenger 📂 Article 📅 2005 🏛 John Wiley and Sons 🌐 English ⚖ 141 KB

## Abstract In this article we present a semi‐supervised active learning algorithm for pattern discovery in information extraction from textual data. The patterns are reduced regular expressions composed of various characteristics of features useful in information extraction. Our major contribution