S3niffer: A text description-based service search system
In this research, we address the problem of retrieving services which fulfil users' need expressed in query in free text. Our goal is to cope the term mismatch problems which affect the effectiveness of service retrieval models applied in prior research on text descriptions-based service retrie...
- Autores:
-
Caicedo Castro, Isaac Bernardo
- Tipo de recurso:
- Doctoral thesis
- Fecha de publicación:
- 2015
- Institución:
- Universidad Nacional de Colombia
- Repositorio:
- Universidad Nacional de Colombia
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.unal.edu.co:unal/54391
- Acceso en línea:
- https://repositorio.unal.edu.co/handle/unal/54391
http://bdigital.unal.edu.co/49323/
- Palabra clave:
- 0 Generalidades / Computer science, information and general works
02 Bibliotecología y ciencias de la información / Library and information sciences
62 Ingeniería y operaciones afines / Engineering
Extracción de información
Factorización de matrices
Descubrimiento de servicios basados en IR
Expansión de consultas
Tesauros de co-ocurrencias
Information retrieval
Matrix factorisation
IR-based service discovery
Query expansion
Co-occurrence thesaurus
La recherche d'information
Factorisation de matrices
Découverte de service basé sur des techniques de RI
Expansion de requêtes
thésaurus co-occurrence
- Rights
- openAccess
- License
- Atribución-NoComercial 4.0 Internacional
Summary: | In this research, we address the problem of retrieving services which fulfil users' need expressed in query in free text. Our goal is to cope the term mismatch problems which affect the effectiveness of service retrieval models applied in prior research on text descriptions-based service retrieval models. These problems are caused due to service descriptions are brief. Service providers use few terms to describe desired services, thereby, when these descriptions are different to the sentences in queries, term mismatch problems decrease the effectiveness in classical models which depend on the observable text features instead of the latent semantic features of the text. We have applied a family of Information Retrieval (IR) models for the purpose of contributing to increase the effectiveness acquired with the models applied in prior research on service retrieval. Besides, we have conducted systematic experiments to compare our family of IR models with those used in the state-of-the-art in service discovery. From the outcomes of the experiments, we conclude that our model based on query expansion via a co-occurrence thesaurus outperforms the effectiveness of all the models studied in this research. Therefore, we have implemented this model in S3niffer, which is a text description-based service search engine. |
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