Towards Automatic Service Level Agreements Information Extraction

6th International Conference on Cloud Computing and Services Science, Rome, Italy, 23-25 April 2016Information systems and computing capabilities are delivered through the Internet in the form of services; they are regulated by a Service Level Agreement (SLA) contract co-signed by a generic Application Service Provider (ASP) and the end user(s), as happens for instance in the cloud. In such a type of contract several clauses are established; they concern the level of the services to guarantee, also known as quality of service (QoS) parameters, and the penalties to apply in case the requirements are not met during the SLA validity time, among others. SLA contracts use legal jargon, indeed they have legal validity in case of court litigation between the parties. A dedicated contract management facility should be part of the service provisioning because of the contractual importance and contents. Some work in literature about these facilities rely on a structured language representation of SLAs in order to make them machine-readable. The majority of these languages are the result of private stipulation between private industries and not available for public services where SLAs are expressed in common natural language instead. In order to automate the SLAs management, the first step is to recognise the documents. In this paper an investigation towards SLAs text recognition is presented; the proposal is driven by an analysis of the contractual contents necessary to be automatically extracted in order to facilitate possible criminal investigations

Towards automatic Service Level Agreements information extraction

Service Level Agreements (SLAs) are contracts co-signed by an Application Service Provider (ASP) and the end user(s) to regulate the services delivered through the Internet. They contain several clauses establishing for example the level of the services to guarantee, also known as quality of service (QoS) parameters and the penalties to apply in case the requirements are not met during the SLA validity time. SLAs use legal jargon, indeed they have legal validity in case of court litigation between the parties. A dedicated contract management facility should be part of the service provisioning because of the contractual importance and contents. Some work in literature about these facilities rely on a structured language representation of SLAs in order to make them machine-readable. The majority of these languages are the result of private stipulation and not available for public services where SLAs are expressed in common natural language instead. In order to automate the SLAs management, in this paper we present an investigation towards SLAs text recognition. We devised an approach to identify the definitions and the constraints included in the SLAs using different machine learning techniques and provide a preliminary assessment of the approach on a set of 36 publicly available SLA documents