The desired services can be measured by the attributes such as accuracy, efficiency and flexibility. Matchmaking techniques We broadly classify the matchmaking techniques into functional based matchmaking, non- functional based matchmaking and hybrid matchmaking techniques as depicted in Fig.
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Matchmaking Techniques Classification 3. Functional based matchmaking techniques The functional based matchmaking matches based on functionalities of the users. It filters the web service advertisements based on the functional restrictions of the user . The functional based matchmaking matches the service requests with the web service advertisements based on the functionalities such as input, output, precondition, effect, operation, objects, tasks, functions, relations, concepts, attributes and so forth.
The steps to be followed in functional based matchmaking are, Step 1: The set of requests from the consumers is designated as where, u in the maximum number of requests. The matchmaker matches the set of requests from the service consumers with the web service advertisements based on the functionalities. The functional based matchmaking is efficient and accurate, it suits the user requirements. It does not consider the quality of services..
The functional based matchmaking can be improved by further filtering the result of functional based matchmaking by non-functional requirements. The functional based matchmaking techniques match based on the functionalities of the users. The functional based matchmaking techniques can be carried out by various approaches are, 3.
Ontology based matchmaking Ontology based matchmaking matches based on the relationship and the reasoning of functionalities of the users. The ontology elements consists of a set of concepts that belong to the ontology, set of attributes that belong to a concept, its interrelations between several concepts, special type of relation, set of instances that belong to the represented ontology and axiomatic expressions in ontology logical statement. Ontology based matchmaking are efficient and accurate compared to the keyword based matchmaking. Ontology based matchmaking matches based on the relationships and it will not check the meanings.
Ontology based matchmaking can be improved by matching semantically based on the ontology model. Ontology-based keyword matching match the keyword based on the relationships. Ontology based keyword matchmaking use the ontology to categorize registries based on domains and characterize them by maintaining the properties of each registry and the relationships. Ontology based conceptual matchmaking is language neutral and matching is based on the categories in a general top level ontolog and conceptual models of particular domains.
Ontology-based intermediate or combined matchmaking: Ontology based intermediate or combined matchmaking matches based on the terminology models recording terms words, collocations, phrases specific to a domain. Ontology based linguistic matchmaking is language specific and matching is based on the vocabulary and relationships between words. Multiple Ontology based matchmaking MOM: Multiple ontology based matchmaking is agent based service ontology and it helps agents finding appropriate service providers.
CM It matches M the constraint parts in service descriptions. The Type match TM matches only the types in the input and output fields of the service advertisements against the correspondent field in the requirements, i. Constraint match CM matches the constraint parts of the service descriptions matches, i. In Exact match EM the types and the constraints are matched exactly, i.
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In Partial match PM both the types and the constraints are matched but not exactly, it matches partially, i. Semantic matchmaking The semantic matchmaking matches meaningfully, the service requests matches the advertisements based on the functionalities of the users in reasonable time. The service discovery improves the discovery process by meaningful and content matchmaking . The five degrees of matching output in semantic matchmaking are exact match, plug-in match, subsume match, intersection match and disjoint match.
Its elucidation and notations are discussed in Table 3. The inputs or outputs of an advertisement are a subset of the inputs or outputs of the requests is plug-in match, i. The inputs or outputs of the requests are a subset of inputs or outputs of an advertisements is subsume match, i. The some of the inputs or outputs of an advertisements match with the some of the inputs or outputs of the requests is intersection match, i. In Disjoint match the inputs or outputs of advertisements do not match with the inputs or outputs of the request, i.
Semantic matchmaking enables the scalability, efficiency and dynamic discovery. Semantic matchmaking does more accurate searches and its additional information aids precision and makes it possible to automatic matching. Semantic matchmaking is complex for the developer matching the appropriate services.
As the semantic matchmaking techniques matches based on the meaning, some relevant services might be eliminated and therefore, partial matches should be considered. Semantic based keyword matchmaking: Semantic-based keyword matchmaking match the keyword meaningfully based on the functionalities of the users. Semantic based matchmaking match the keyword given by the user with the advertisement, semantically.
Semantic based keyword matchmaking quickly matches the huge amount of available goal and service descriptions. Semantic based keyword matchmaking improves the efficiency and accuracy. The corpus based matchmaking  matches between WSDL files. The corpus based matchmaking is used in identifying the semantic similarity between the two WSDL files.
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The corpus based matchmaking matches all the possible pairs of elements from the two WSDL files. A corpus of web documents belongs to the functional domain of the WSDL files in which one corpus is associated with one web service functional domain. Corpus based matchmaking is ineffective way to automate the pre-process of the WSDL files.
It has complex names e. It considers only semantic similarities, whereas the structural information such as parent-child relationship, number of children, etc.
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Hybrid semantic web service matchmaker for OWL-S services: It significantly improves the incorporating non-logic-based information retrieval techniques. It increases the efficiency and accuracy. The behavioral matchmaking matches based on the specification of service behavior. This is the matching approach that operates on behavior models, allows delivery of partial matches and evaluation of semantic distance between these matches and the user requirements .
Compared to semantic matchmaking which eliminates the partial information, this problem can be avoided by behavioral matchmaking which is efficient, in turn. In behavioral matchmaking the indexing and filtering reduces the search space and complexity. Ontology based semantic matchmaking In ontology based semantic matchmaking the request semantically matches the services based on the ontology model. In ontology based semantic matchmaking, the service requesters and service providers use ontology to discover similarities between two services.
Ontology based semantic matchmaking improves the efficiency and accuracy of matchmaking. This ontology based semantic matchmaking is more flexible and its dynamic matching mechanism is based on semantic descriptions stored in ontologies. Ontology-based semantic linguistic matchmaking: Ontology based semantic linguistic matchmaking is language specific, matching is based on the semantic lexicons recording vocabulary and relationships between words.
Description logic in ontology based semantic matchmaking: Description logic is the family of knowledge representation formalisms. Ontology based semantic matchmaking is the semantic matching based on OWL DL ontology where the advertisements and requests refer to OWL concepts and the associated semantics, or are expressed in Description Logic based expressions or formalisms . Description logic in ontology based semantic matchmaking improves the quality of matchmaking. To improve matchmaking the background knowledge as rules can be used to enrich the description of concepts.
The key based matchmaking matches the service requests with the web service advertisements based only on the keywords. It does not match based on the relationship and the meaning between the words.
So in the keyword based matchmaking the accuracy and efficiency is less. The complexity is in terms of effort, effort taken for matchmaking the user request with the advertisements based on the keyword is less. To match the complex services the keyword based matchmaking is not more effective. Semantic based matchmaking matches meaningfully so the efficiency and accuracy is high and complexity is high as it matching meaningfully, and it is better in complex matchmaking services.
The ontology based semantic matchmaking which matches semantically in ontology model with more efficiency and accuracy, the complexity is moderate and is best in complex matchmaking services. Deductive matchmaking In deductive matchmaking the description of requests matches with the description of advertisements.
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