Triple Rules Research Articles

A Joint Entity-Relation Detection and Generalization Method Based on Syntax and Semantics for Chinese Intangible Cultural Heritage Texts

Annotation of a natural language corpus not only facilitates researchers in extracting knowledge from it but also helps achieve deeper mining of the corpus. However, an annotated corpus in the humanities knowledge domain is lacking. In addition, the semantic annotation of humanities texts is difficult, because it requires a high domain background for researchers and even requires the participation of domain experts. Based on this, this study proposes a method for detecting entities and relations in a domain that lacks an annotated corpus, as well as provides a referenceable idea for constructing conceptual models based on textual instances. Based on syntactic and semantic features, this study proposes SPO triple recognition rules from the perspective of giving priority to predicates and generalization rules from the perspective of a triple’s content and the meaning of its predicate. The recognition rules are used to extract text-descriptive SPO triples centered on predicates. After clustering and adjusting triples, the generalization rules proposed in this study are used to obtain coarse-grained entities and relations, and then form a conceptual model. This study recognizes SPO triples with high precision and summarization from descriptive texts, generalizes them, and then forms a domain conceptual model. Our proposed method provides a research idea for entity-relation detection in a domain with a missing annotated corpus, and the formed domain conceptual model provides a reference for building a domain Linked Data Graph. The feasibility of the method is verified through practice on texts related to the four traditional Chinese festivals.

SEMANTIC GRAPH KNOWLEDGE REPRESENTATION FOR AL-QURAN VERSES BASED ON WORD DEPENDENCIES

Semantic approaches present an efficient, detailed and easily understandable representation of knowledge from documents. Al-Quran contains a vast amount of knowledge that needs appropriate knowledge extraction. A semantic based approach can help in designing an efficient and explainable knowledge representation model for Al-Quran. This research aims to propose a semantic-graph knowledge representation model for verses of Al-Quran based on word dependencies. These features are used in the proposed knowledge representation model allowing the semantic graph matching to improve Al-Quran search applications' accuracy. The proposed knowledge representation model is essentially a formalism for generating a semantic graph representation of Quranic verses, which can be applied for knowledge base construction for other applications such as information retrieval system. A set of rules called Semantic Dependency Triple Rules are defined to be mapped into the semantic graph representing the verse's logic. The rules translate word dependencies and other NLP metadata into a triple form that holds logical information. The proposed model has been tested with English translation of Al-Quran on a document retrieval prototype The basic system has been enhanced with anaphoric pronouns correction, which has shown improvement in retrieval performance. The results have been compared with a closely related system and evaluated on the accuracy of the document retrieval in Precision, Recall and F-score measurements. The proposed model has achieved 65%, 60% and 62.4% for the measurements, respectively. It has also improved the overall accuracy of previous system by 43.8%.

Wettability of Carbonate Reservoir Rocks: A Comparative Analysis

Various methods have been proposed for the evaluation of reservoir rock wettability. Among them, Amott–Harvey and USBM are the most commonly used approaches in industry. Some other methods, such as the Lak and modified Lak indices, the normalized water fractional flow curve, Craig’s triple rules of thumb, and the modified Craig’s second rule are based on relative permeability data. In this study, a set of capillary pressure curves and relative permeability experiments was conducted on 19 core plug samples from a carbonate reservoir to evaluate and compare different quantitative and qualitative wettability indicators. We found that the results of relative permeability-based approaches were consistent with those of Amott–Harvey and USBM methods. We also investigated the relationship between wettability indices and rock quality indicators RQI, FZI, and Winland R35. Results showed that as the rock quality indicators increased, the samples became more oil-wet.

A MODEL FOR EVALUATING THE RISK EFFECTS ON CONSTRUCTION PROJECT ACTIVITIES

Cost overruns and time delays are considered to be very important challenges for the majority of construction projects. These challenges are typically attributed to their associated risks. Due to the risky and uncertain nature of construction projects, an increasing amount of attention is given to estimating and overcoming cost overruns and time delays. New techniques are being developed to help project managers to contractually complete projects within cost and time constraints. The objective of this study was to develop a new qualitative and quantitative risk analysis model that can be employed for construction projects. The proposed model, which is based on a fuzzy logic tool, consists of two modules for assessing risk factors that affect the main construction activities and computing the expected cost overruns and time delays that are associated with these risks. Using numerous logical rules, the model applies the probability of occurrences and impacts of the risks on the cost and time of the main activities. The Spearman and Kendall correlation coefficient tests are applied to verify and select a suitable membership function. Using four proposed membership functions, the results of these tests confirmed that the triangle membership function is suitable for the model. The model is verified by application to HVAC system activities in two actual construction projects, which serve as case studies. Two different methods are proposed and applied to quantify the cost overruns and time delays. The first method is based on determining the cost overruns and time delay values for each activity according to their weight in the system. Triple premise rules are proposed and applied in the second method, which is established to relate all activities. The results from the second method are more accurate compared with the first method based on actual data from the case study projects. In addition, the results demonstrated that the proposed model can be used to quantify the expected cost overrun and time delays in construction project activities and can be generalized and implemented in different construction activities.

Visual Modeling and Analysis of EMF Model Transformations Based on Triple Graph Grammars

The tool HENSHIN is an Eclipse plug-in supporting visual modeling and execution of rule-based EMF model transformations. This paper describes the re- cent extensions of HENSHIN by a visual editor for triple graph grammars (TGGs). The visual editor (called HENSHINTGG) supports a compact visualization of triple rules in an integrated editor panel. Internally, triple graph rules are represented as HENSHIN rules and can be simulated using the HENSHIN EMF model transforma- tion engine. Our extension supports the automatic generation of forward translation rules for transforming source into target models. A converter from HENSHIN TGG rules to the graph transformation analysis tool AGG allows a systematic check for conflicts of forward translation rules in AGG based on critical pair analysis.

Formal Specification of Model Transformations by Triple Graph Grammars with Application Conditions

Triple graph grammars are a successful approach to describe exogenous model transformations, i.e. transformations between models conforming to differ- ent meta-models. Source and target models are related by some connection part, triple rules describe the simultaneous construction of these parts, and forward and backward rules can be derived modeling the forward and backward model transfor- mations. As shown already for the specification of visual models by typed attributed graph transformation, the expressiveness of the approach can be enhanced signifi- cantly by using application conditions, which are known to be equivalent to first order logic on graphs. In this paper, we extend triple rules with a specific form of application conditions, which enhance the expressiveness of formal specifications for model transforma- tions. We show how to extend results concerning information preservation, termi- nation, correctness, and completeness of model transformations to the case with application conditions. We illustrate our approach and results with a model trans- formation from statecharts to Petri nets.

Specification and Verification of Model Transformations

Model transformations are a key concept within model driven development and there is an enormous need for suitable formal analysis techniques for model transformations, in particular with respect to behavioural equivalence of source models and their corresponding target models. For this reason, we discuss the general challenges that arise for the specification and verification of model transformations and present suitable formal techniques that are based on graph transformation. In this context, triple graph grammars show many benefits for the specification process, e.g. modelers can work on an intuitive level of abstraction and there are formal results for syntactical correctness, completeness and efficient execution. In order to verify model transformations with respect to behavioural equivalence we apply well-studied techniques based on the double pushout approach with borrowed context, for which the model transformations specified by triple graph transformation rules are flattened to plain (in-situ) graph transformation rules. The potential and adequateness of the presented techniques are demonstrated by an intuitive example, for which we show the correctness of the model transformation with respect to bisimilarity of source and target models.

Automating the transformation-based analysis of visual languages

Abstract We present a novel approach for the automatic generation of model-to-model transformations given a description of the operational semantics of the source language in the form of graph transformation rules. The approach is geared to the generation of transformations from Domain-Specific Visual Languages (DSVLs) into semantic domains with an explicit notion of transition, like for example Petri nets. The generated transformation is expressed in the form of operational triple graph grammar rules that transform the static information (initial model) and the dynamics (source rules and their execution control structure). We illustrate these techniques with a DSVL in the domain of production systems, for which we generate a transformation into Petri nets. We also tackle the description of timing aspects in graph transformation rules, and its analysis through their automatic translation into Time Petri nets.

Triple patterns: Compact specifications for the generation of operational triple graph grammar rules

Triple Graph Grammars (TGGs) allow the specification of high-level rules modelling the synchronized creation of elements in two graphs related through a correspondence graph. Low-level operational rules are then derived to manipulate concrete graphs. However, TGG rules may become unnecessarily verbose when elements have to be replicated from one graph to the other, and their actual derivation cannot exploit the presence of reoccurring patterns. Moreover they do not take advantage from situations in which a normal creation grammar for one of the graphs exists, from which TGG operational rules can be derived to build the other graph. We present an approach to generating TGG operational rules from normal ones, reducing the information needed to derive them, through the definition of Triple Patterns, a high-level, compact, declarative, and visual notation for the description of admissible structures in a triple graph. Patterns can be expressed with respect to classes defined in a meta-model, and instantiated with derived classes at the model level, thus exploiting the inheritance hierarchies. The application of the generated rules results into the (synchronized or batch) creation of the structures specified in the patterns. We illustrate these concepts by showing their application to the synchronized incremental construction of visual models and of their semantics.

Generation of Advanced Modelling Environments by Means of Graph Transformation Techniques

In this paper we show our approach to the automatic generation of modelling environments for Visual Languages (VLs) supporting multiple views. The approach is based on the meta-modelling tool AToM3. Starting from a meta-model description of the VL and its views, a customized modelling environment is generated. Consistency between views is supported by the automatic generation of triple graph grammar rules that build a unique model “gluing” all the view models. Moreover, the generated environments allow taking basic static metrics of the models. Extreme values of the metrics may trigger heuristics for the refactoring of the models. These heuristics are formalized in the form of graph grammar rules. We show the application of these concepts in the area of hypermedia design by generating an environment for the Labyrinth VL.