A company who wishes to enter an established marked with a new, competitive product is required to analyse the product solutions of the competitors. Identifying and comparing the features provided by the other vendors might greatly help during the market analysis. However, mining common and variant features of from the publicly available documents of the competitors is a time consuming and error-prone task. In this paper, we suggest to employ a natural language processing approach based on contrastive analysis to identify commonalities and variabilities from the brochures of a group of vendors. We present a first step towards a practical application of the approach, in the the context of the market of Communications-Based Train Control (CBTC) systems.
Mining commonalities and variabilities from natural language documents / Alessio Ferrari;Giorgio O. Spagnolo;Felice Dell'Orletta. - STAMPA. - (2013), pp. 116-120. (Intervento presentato al convegno 17th International Software Product Line Conference on - SPLC '13) [10.1145/2491627.2491634].
Mining commonalities and variabilities from natural language documents
FERRARI, ALESSIO;SPAGNOLO, GIORGIO ORONZO;
2013
Abstract
A company who wishes to enter an established marked with a new, competitive product is required to analyse the product solutions of the competitors. Identifying and comparing the features provided by the other vendors might greatly help during the market analysis. However, mining common and variant features of from the publicly available documents of the competitors is a time consuming and error-prone task. In this paper, we suggest to employ a natural language processing approach based on contrastive analysis to identify commonalities and variabilities from the brochures of a group of vendors. We present a first step towards a practical application of the approach, in the the context of the market of Communications-Based Train Control (CBTC) systems.I documenti in FLORE sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.