This paper presents the platform targeted in the PROGRESS-IT project. It represents an Enterprise Semantic Search engine tailored for Small and Medium Sized Enterprises to retrieve information about Projects, Grants, Patents or Scientific Papers. The proposed solution improves the usability and quality of standard search engines through Distributional models of Lexical Semantics. The quality of the Keyword Search has been improved with Query Suggestion, Expansion and Result Re-Ranking. Moreover, the interaction with the system has been specialized for the analysts by defining a set of Dashboards designed to enable richer queries avoiding the complexity of their definition. This paper shows the application of Linguistic Technologies, such as the Structured Semantic Similarity function to measure the relatedness between documents. These are then used in the retrieval process, for example to ask the system for Project Ideas directly using an Organization Description as a query. The resulting system is based on Solr, inheriting its highly reliability, scalability and fault tolerance, providing distributed indexing, replication and load-balanced querying, automated failover and recovery, centralized configuration and more.

Basili, R., Ciapetti, A., Croce, D., Marino, V., Salvatore, P., Storch, V. (2014). Enabling enterprise semantic search through language technologies: The progressit experience. In CEUR Workshop Proceedings (pp.51-62). CEUR-WS.

Enabling enterprise semantic search through language technologies: The progressit experience

BASILI, ROBERTO;CROCE, DANILO;
2014-01-01

Abstract

This paper presents the platform targeted in the PROGRESS-IT project. It represents an Enterprise Semantic Search engine tailored for Small and Medium Sized Enterprises to retrieve information about Projects, Grants, Patents or Scientific Papers. The proposed solution improves the usability and quality of standard search engines through Distributional models of Lexical Semantics. The quality of the Keyword Search has been improved with Query Suggestion, Expansion and Result Re-Ranking. Moreover, the interaction with the system has been specialized for the analysts by defining a set of Dashboards designed to enable richer queries avoiding the complexity of their definition. This paper shows the application of Linguistic Technologies, such as the Structured Semantic Similarity function to measure the relatedness between documents. These are then used in the retrieval process, for example to ask the system for Project Ideas directly using an Organization Description as a query. The resulting system is based on Solr, inheriting its highly reliability, scalability and fault tolerance, providing distributed indexing, replication and load-balanced querying, automated failover and recovery, centralized configuration and more.
5th Italian Information Retrieval Workshop, IIR 2014
ita
2014
Rilevanza nazionale
Settore ING-INF/05 - Sistemi di Elaborazione delle Informazioni
Settore INF/01 - Informatica
English
Computer Science (all)
http://ceur-ws.org/
Intervento a convegno
Basili, R., Ciapetti, A., Croce, D., Marino, V., Salvatore, P., Storch, V. (2014). Enabling enterprise semantic search through language technologies: The progressit experience. In CEUR Workshop Proceedings (pp.51-62). CEUR-WS.
Basili, R; Ciapetti, A; Croce, D; Marino, V; Salvatore, P; Storch, V
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2108/124121
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