Semantic technologies in content management systems pdf

View 1 excerpt, cites methods. Flexible Learning Object Metadata. View 2 excerpts, cites background and methods. A context-aware adaptive learning system using agents. Expert Syst. Generating context-related feedback for teachers. The paper presents LOCO-Analyst, an educational tool for providing teachers with fine-grained and context-rich feedback.

Such an advanced feedback enables teachers to rethink the content and … Expand. An open IMS-based user modelling approach for developing adaptive learning management systems. Collection is a class that represents physical collections of objects. A collection may impose a cer- tain order to be followed during a visit to contained LOs.

Thus, the model specializes the collection class into: set, bag, list or hierarchy. Set and list represent the corresponding mathematical concepts, whereas bags may contain duplicates in the collection. Hierarchy corresponds to LOs whose contents follow a tree structure. The set and bag classes include attributes to identify maximum and minimum cardinalities. Those attributes introduce restrictions over the collections that specify, respectively, the maximum and minimum number of elements that may be extracted from the collection.

In Figure 1, for instance, the exclusive or aggregation relationship between Relational Calculus and QUEL and QBE can be modeled by a set collection with maximum cardinality 1 and minimum cardinality 1, meaning that at least one and at maximum one of the LOs in the set should be exhibited when present- ing Relational Calculus.

Associations among LOs, whose cardinality is typically one to many, are modeled as relationship collections, which inherit both from Relationship and Collection classes conceptually define triples t subject, property, object , extended to n-ary relationships, where subject and objects are of type LO and property is a relationship. The schema specifies valid associations through triples T class, rela- tionship type, class.

Thus, valid instances of t are in accordance to T. User queries may join LOs from different database collections or database repository , according to a certain boolean predicate. The Inner collection Class presents the similar concept of tuple in the rela- tional model. It is used to support combination of LOs resulted from a join operation. For pairs of LOs that agree on the join predicate, an inner collection is formed containing both LOs.

Initially, when a LO is retrieved from a repository a single LO inner collection is created to hold it. Subsequent join operations would eventually fill inner collection with joined LOs. The data model, nevertheless, differ from RDF data model. Hence, attribute values are not identifi- able and are not considered first class objects, as in the case of literals in RDF [6]. Aggregation and semantic relationships are modeled as collections of LOs. This is more general than in RDF, since it requires a bag resource and a specific list of predicates to model collections, leading to a complex representation and query evaluation.

When representing, for example, the predicate covers of Figure 4a, which associates Query Language to Re- lational Algebra and Calculus in RDF, it is not possible to ensure that all the collection members would be visited when reaching the Query Language LO.

On the other hand, the proposed model con- siders the collection members as a whole unit, as shown in Figure 4b, assuring that all its elements are effectively visited. So users may query associations and data indistinctly. The algebra definition makes it possible to express a high-level query language into a formal canonical representation, as well as the conception of optimization strategies.

Many algebras have been proposed covering operations in different data models [4,5,13,14,6,7,]. This work presents an algebra, which, in some sense, borrows from all these works. Firstly, the major- ity of the operators are adapted from their relational algebra counterparts. Path expressions through LO relationships are similar to path expressions in the OO data model [5]. In this algebra, operators receive collections of LOs as input and equally produce collections of LOs as output.

The closure of the model enables the composition of operators in an algebra expression. The algebra includes operators to explore relationships between LOs as one of the semantic enrich- ments provided by the proposed model. This is achieved by exploring relationship type equivalence properties within the semantics of navigation operators. Relationships of aggregation type receive spe- cial treatment once their transitive property is known to the systems. Operators over domain specific type of relationships consider the equivalence class of its corresponding relationship type, such as: re- flexive, symmetric and transitive.

As an example, reflexive predicates include, implicitly, the associa- tion between a LO and itself through that predicate. Transitive predicates make it possible the evalua- tion of transitive closure operators and a symmetric predicate enables answering queries independently of the LO role in an association, as subject or object. The algebra includes operators to manipulate ob- jects and collections selection and project operators, etc.

The system also includes a QBE like environment for submitting queries following a user- friendly interface.

Its behavior is defined by the pi term according to the algebra. In the absence of the from clause, a collection c may be specified as a source for the database collection. A collection is speci- fied by a pair schema, class where schema E identifies a database and class c is the col- lection class.

A list of n terms in this clause should be followed by n-1 join predicates be- tween the collections. An instance variable v may be defined to iterate over a collection, in which case a selection may restrict the collection elements. Selections may be specified over LOs metadata attributes, or over relationship identifications. The user may also write path-expressions to navigate through a list of relationships and define a terminal collection over which a predicate would operate.

The input collection may be specified in the from clause in conjunction with the where clause or directly in the start clause. The in- ference stops when one of the events occurs: no more relationships to follow; no new LOs are obtained; a limit of recursion is achieved. RDF Resource Description Framework can be used for describing the web resources and the relationship between them. Resources can be any object about which we would think. A resource may be an author or a book or a publisher and so on.

Properties are special kinds of resources which describe the relation between the resources. Statements assert or declare the properties of resources.

A statement in RDF is Object-Property- Value triple consisting of a resource Object , property the property of the resource and value is the property value of the resource [4]. So Compared to XML and relational databases, which are structural-oriented, RDF takes into consideration a knowledge oriented approach that is designed specifically for the Web and that is extremely useful for the Semantic Web. In offline ontology extraction, the system extracts the explicit classes and relations from the relational schema.

Then the domain expert will adapt the extracted ontology by adding the implicit relations to complete the ontology. In online query operation the user can issue a semantic query to the system, and the system maps that query into a related SQL query for the underlining relational database. Every Library has books with unique id, title, author, price and status available or not. Library also maintains the details of publishers of the books including the publisher id, name and address.

The database also maintains the complete book details and issue details. The complete Relational Database of the Library Management System considered can be shown in table below.

Rule1: If the primary key of any relation is unique and do not contain the primary key of any other relation then we consider such relation as on ontological class. As per our Library example Member and Publisher are separate Ontological classes. Mid,Mname,Addr,Mtype lib:Publisher rdf:type rdfs:class. As per our Library example members borrow books from library so Borrowerid from Borrow can be an object property with domain as Member and range as Book.

Many more rules of such type can be applied to extract the ontology from the relational database. Following figure shows the extracted ontology where all the class and the data type properties are defined but some object type properties are not yet defined. This stage will add the explicit definition of the implicit relationships and adjust directions of the object properties between classes.

For example the property relation between the Book and Publisher classes is not fully defined yet. Here lib is the namespace for the extracted ontology 4.

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