e-Learning plays an undoubtedly important role in today's education and assessment is one of the most essential parts of any instruction-based learning process. Assessment is a common way to evaluate a student's knowledge regarding the concepts related to learning objectives. In this paper, a new method for assessing the free text answers of students based on the BLEU algorithm is presented. We modify the BLEU algorithm so that it is suitable for assessing free text answers and call the new algorithm the modified BLEU (M-BLEU). To perform an assessment, it is necessary to establish a repository of reference answers written by course instructors or related experts. Several reference answers are included for each question. The M-BLEU algorithm is used to identify the most similar reference answer to a student answer; a similarity score is calculated and applied to score the answers provided by students. Evaluation results show that the proposed method achieves the highest correlation with human expert scores compared to other assessment methods such as latent semantic analysis (LSA) and n-gram co-occurrence.

The automatic assessment of free text answers using a modified BLEU algorithm

EXtensible Markup Language (XML) has emerged as the dominant standard in describing and exchanging data among heterogeneous data sources. The increasing presence of large volumes of data appearing creates the need to investigate XML Document Warehouses as a means of handling the data. In this paper our focus is twofold. First we utilise Object Oriented (OO) concepts to develop and propose a conceptual design formalism to build meaningful XML Document Warehouses (XDW). This includes: (1) XML (warehouse) repository (xFACT) using OO concepts followed by the transformation of XML Schema constructs and (2) Conceptual Virtual Dimensions (VDims) using Conceptual views (Rajugan, Chang, Dillon, & Feng, 2003, 2004). Secondly we address several important outstanding issues related to our proposed design of an XML Document Warehouse. Specifically we note that the xFACT portion is now a complex structure, involving several entities and relationships as opposed to being a simple FACT table as was the case in relational data warehouses, and the notion of Virtual Dimensions (VDims) has considerably greater complexity.

Conceptual and Systematic Design Approach for XML Document Warehouses

EXtensible Markup Language (XML) has emerged as the dominant standard in describing and exchanging data among heterogeneous data sources. XML with its self-describing hierarchical structure and its associated XML Schema (XSD) provides the flexibility and the manipulative power needed to accommodate complex, disconnected, heterogeneous data. The issue of large volume of data appearing deserves investigating XML Document Warehouses. But due to XML's non-scalar, set-based semi-structured nature, traditional data design models lack the ability to represent XML design level constructs in an and implementation-independent form which are crucial for designing complex domains such as data marts and data warehouses, but also during their operational and maintenance phase. We utilize Object Oriented (OO) concepts to develop a conceptual model for XML Document Warehouses. In this paper we propose a conceptual design formalism to build meaningful XML Document Warehouses (XDW). Our focus includes; (1) conceptually design and build meaningful XML (warehouse) repository (xFACT) using OO concepts in integration with XML Schema constructs, (2) conceptually model and design virtual dimensions using XML conceptual views [10a] [lOb] to satisfy warehouse end-user requirements and (3) use UML package diagrams to help logically group and build hierarchical conceptual views to enhance semantics and expressiveness of the XDW.

Conceptual design of XML document warehouses

In this position paper, we discuss how different branches of research on clustering and pattern mining, while rather different at first glance, in fact have a lot in common and can learn a lot from each other's solutions and approaches. We give brief introductions to the fundamental problems of different sub-fields of clustering, especially focusing on subspace clustering, ensemble clustering, alternative (as a variant of constraint) clustering, and multiview clustering (as a variant of alternative clustering). Second, we relate a representative of these areas, subspace clustering, to pattern mining. We show that, while these areas use different vocabularies and intuitions, they share common roots and they are exposed to essentially the same fundamental problems; in particular, we detail how certain problems currently faced by the one field, have been solved by the other field, and vice versa.

The purpose of our survey is to take first steps towards bridging the linguistic gap between different (sub-) communities and to make researchers from different fields aware of the existence of similar problems (and, partly, of similar solutions or of solutions that could be transferred) in the literature on the other research topic.

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The blind men and the elephant: on meeting the problem of multiple truths in data from clustering and pattern mining perspectives

Existing systems for XML views only support selection operation applied in the views and cannot validate views. In this paper, we propose a systematic approach to design valid XML views. First, we transform the semistructured XML source documents into a semantically rich Object-Relationship-Attribute model designed for SemiStructured data (ORA-SS). Second, we enrich the ORA-SS diagram with semantics such as participation constraints of object classes and distinguishing between attributes of object classes and relationship types, which cannot be expressed in the XML document. Third, we use the additional semantics to develop a set of rules to guide the design of valid XML views. We identify four transformation operations for creating XML views, namely, selection, projection, join and swap operation. Finally, we develop a comprehensive algorithm that checks for the validity of XML views constructed by applying the four operations.

Designing valid XML views

Tree model guided candidate generation for mining frequent subtrees from XML

For complex industrial informatics applications, there exists a requirement to model and design views at a higher level of abstraction. Since the classical view definitions are only available at the data, query or instance level, modelling and maintaining views for such complex systems is an impossible task. With the introduction of XML and XML Schema and their rapid adaptation by the commercial and industrial systems increased the complexity further for view design and specification. In this paper we present a methodology for modelling and transforming conceptual views into XML views using a modified semantic network called XML Semantic Net (XSemantic Net). Here we extend the work with a rich set of conceptual operators to enable systematic construction of conceptual views. First the semantic modelling of conceptual view is enabled by using XSemantic nets and its conceptual operators. Then we enable systematic mapping of conceptual views into XML views (logical level) by providing a set of transformation rules between XSemantic nets and XML (view) Schema.

XML views. Part II. Modeling conceptual views using XSemantic nets

In industrial informatics, there exists a requirement to model and design views at a higher level of abstraction. Since the classical view definitions are only available at the query or instance level, modelling and maintaining such views for complex enterprise information systems (EIS) is a challenging task. Further, the introduction of semi-structured data (namely XML) and its rapid adaptation by the commercial and industrial systems increased the complexity for view design and specification. To address such and issue, in this paper we present; (a) a layered view model for XML, (b) a design methodology for such views and (c) some real-world industrial applications of the view model. The XML view formalism is defined at the conceptual level and the design methodology is based on the XML semantic (XSemantic) nets, a high-level object-oriented (OO) modelling language for XML domains.

L. Feng

Papers

Tree model guided candidate generation for mining frequent subtrees from XML

XML views. Part II. Modeling conceptual views using XSemantic nets

Semantic modeling of e-solutions using a view formalism with conceptual & logical extensions