The relational Model of Data is based on the concept of a Relation.
A Relation is a mathematical concept based on the ideas of sets.
The strength of the relational approach to data management comes from the formal foundation provided by the theory of relations.
We review the essentials of the relational approach in this chapter.
A minimally supervised machine learning framework is described for extracting relations of various complexity. Bootstrapping starts from a small set of n-ary relation instances as “seeds”, in order to automatically learn pattern rules from parsed data, which then can extract new instances of the relation and its projections. We propose a novel rule representation enabling the composition of n-ary relation rules on top of the rules for projections of the relation.
A complex relation is any n-ary relation in which some of the arguments may be be unspeciﬁed. We present here a simple two-stage method for extracting complex relations between named entities in text. The ﬁrst stage creates a graph from pairs of entities that are likely to be related, and the second stage scores maximal cliques in that graph as potential complex relation instances. We evaluate the new method against a standard baseline for extracting genomic variation relations from biomedical text. ing named entities.
Many errors produced by unsupervised and semi-supervised relation extraction (RE) systems occur because of wrong recognition of entities that participate in the relations. This is especially true for systems that do not use separate named-entity recognition components, instead relying on general-purpose shallow parsing. Such systems have greater applicability, because they are able to extract relations that contain attributes of unknown types. However, this generality comes with the cost in accuracy.
Web geometry is devoted to the study of families of foliations which are in general position. We restrict ourselves to the local situation, in the neighborhood of the origin in C2 , with d ≥ 1 complex analytic foliations of curves in general position. We are interested in the geometry of such conﬁgurations, that is, properties of planar d-webs which are invariant with respect to analytic local isomorphisms of C2 . The initiators of the subject are W. Blaschke, G. Thomsen and G. Bol in the 1930’s (cf. [B-B], [B] and for instance [H1]). ...
We present a novel approach to discovering relations and their instantiations from a collection of documents in a single domain. Our approach learns relation types by exploiting meta-constraints that characterize the general qualities of a good relation in any domain. These constraints state that instances of a single relation should exhibit regularities at multiple levels of linguistic structure, including lexicography, syntax, and document-level context.
Creating labeled training data for relation extraction is expensive. In this paper, we study relation extraction in a special weakly-supervised setting when we have only a few seed instances of the target relation type we want to extract but we also have a large amount of labeled instances of other relation types. Observing that different relation types can share certain common structures, we propose to use a multi-task learning method coupled with human guidance to address this weakly-supervised relation extraction problem. ...
This paper describes a novel event-matching strategy using features obtained from the transitive closure of dependency relations. The method yields a model capable of matching events with an F-measure of 66.5%. training and test instance in a feature space. Conceptually, our features are of three diﬀerent varieties. This section describes the ﬁrst two kinds, which we call “low-level” features, in that they attempt to capture how much of the basic information of an event e is present in a sentence s. 2.1 Lexical features ...
We present a simple linguistically-motivated method for characterizing the semantic relations that hold between two nouns. The approach leverages the vast size of the Web in order to build lexically-speciﬁc features. The main idea is to look for verbs, prepositions, and coordinating conjunctions that can help make explicit the hidden relations between the target nouns.
In this paper, we present Espresso, a weakly-supervised, general-purpose, and accurate algorithm for harvesting semantic relations. The main contributions are: i) a method for exploiting generic patterns by filtering incorrect instances using the Web; and ii) a principled measure of pattern and instance reliability enabling the filtering algorithm. We present an empirical comparison of Espresso with various state of the art systems, on different size and genre corpora, on extracting various general and specific relations.
Information Extraction (IE) is a fundamental technology for NLP. Previous methods for IE were relying on co-occurrence relations, soft patterns and properties of the target (for example, syntactic role), which result in problems of handling paraphrasing and alignment of instances. Our system ARE (Anchor and Relation) is based on the dependency relation model and tackles these problems by unifying entities according to their dependency relations, which we found to provide more invariant relations between entities in many cases. ...
Most information extraction systems either use hand written extraction patterns or use a machine learning algorithm that is trained on a manually annotated corpus. Both of these approaches require massive human effort and hence prevent information extraction from becoming more widely applicable. In this paper we present URES (Unsupervised Relation Extraction System), which extracts relations from the Web in a totally unsupervised way.
We present a novel hybrid approach for Word Sense Disambiguation (WSD) which makes use of a relational formalism to represent instances and background knowledge. It is built using Inductive Logic Programming techniques to combine evidence coming from both sources during the learning process, producing a rule-based WSD model. We experimented with this approach to disambiguate 7 highly ambiguous verbs in EnglishPortuguese translation.
This paper describes a novel instancebased sentence boundary determination method for natural language generation that optimizes a set of criteria based on examples in a corpus. Compared to existing sentence boundary determination approaches, our work offers three signiﬁcant contributions. First, our approach provides a general domain independent framework that effectively addresses sentence boundary determination by balancing a comprehensive set of sentence complexity and quality related constraints.
Psychology is the Science of Mental Life, both of its phenomena and of their conditions. The
phenomena are such things as we call feelings, desires, cognitions, reasonings, decisions, and the
like; and, superficially considered, their variety and complexity is such as to leave a chaotic
impression on the observer.
Nevertheless, vitalism continued to find its way into the description of life
processes. For instance, Pasteur writing about his discovery of the importance of
oxygen availability for sugar fermentation by yeast, to be later known as the Pasteur
effect, argued for the exclusive dependency of intact cell structure, a variant of cell
theory postulated by Matthias Schleiden, Theodor Schwann, and their predecessors,
and “ferments”, a set of biocatalysts represented as vital forces.
These guidelines shall be included in all research that Aboriginal Women’s Health
It shall be the responsibility, in the first instance, of all researchers to observe these
guidelines to monitor the implementation of the guidelines and to make decisions regarding
their interpretation and application.
ALRI mortality from SFU has most likely declined in the last decades, and is likely to
decline further even without a reduction in SFU or adoption of improved stoves. This
comes about from a reduction in ALRI case fatality rates through for instance improved
case management and reduction in malnutrition rates even in the event that incidence of
morbidity does not decline.
Additional solutions that improve business continuity and availability for Oracle
RAC in an Oracle Virtual Machine environment include Oracle VM Live Migration
and Oracle RAC One Node Online Database Relocation
Oracle VM Live Migration moves a virtual machine from one physical node to
another, within the same pool of servers. Oracle RAC One Node Online Database
Relocation moves an Oracle database instance from one server to another within the
same cluster. In Oracle VM environments, these servers are virtual machines, which
host an Oracle Clusterware based cluster.
The last point, which is in some ways the most important, is the need for
consistency across projects in the same sector. The Portfolio Review found
from the experience in sectoral projects, for example water and sanita-
tion, that in some cases communities, even very poor communities, have
been willing, indeed anxious, to contribute to a service that would meet
their needs and that they knew they would receive.