Identifying rapidly evolving technological trends for R&D planning using SAO-based semantic patent networks

Abstract

Patents constitute an up-to-date source of competitive intelligence in technological development; thus, patent analysis has been a vital tool for identifying technological trends. Patent citation analysis is easy to use, but fundamentally has two main limitations: (1) new patents tend to be less cited than old ones and may miss citations to contemporary patents; (2) citation-based analysis cannot be used for patents in databases which do not require citations. Naturally, citation-based analysis tends to underestimate the importance of new patents and may not work in rapidly-evolving industries in which technology life-cycles are shortening and new inventions are increasingly patented worldwide. As a remedy, this paper proposes a patent network based on semantic patent analysis using subject-action-object (SAO) structures. SAO structures represent the explicit relationships among components used in a patent, and are considered to represent key concepts of the patent or the expertise of the inventor. Based on the internal similarities between patents, the patent network provides the up-to-date status of a given technology. Furthermore, this paper suggests new indices to identify the technological importance of patents, the characteristics of patent clusters, and the technological capabilities of competitors. The proposed method is illustrated using patents related to synthesis of carbon nanotubes. We expect that the proposed procedure and analysis will be incorporated into technology planning processes to assist experts such as researchers and R&D policy makers in rapidly-evolving industries.

A Function-Based Knowledge Base for Technology Intelligence

“…An SAO structure is a syntactically ordered sentence comprising a subject (noun phrase), an action (verb phrase), and an object (noun phrase), and it represents the clear relationship between a subject and an object using an action (Yoon and Kim, 2011). In an SAO structure, S and O may refer to components of the system, and A may refer to functions performed by and on the components (Cascini et al, 2004).…”

Mapping the evolving patterns of patent assignees’ collaboration networks and identifying the collaboration potential

“…Indeed, except for the above methods, there are more complicated topic models could be used for analysing the topics of assignees, then the results could be applied for count P[sim topic (a,b) t-1 ]. Such representative topic models included Latent Dirichlet Allocation (LDA) model (Blei, Ng and Jordan, 2003) and Subject-Action-Object (SAO) model (Yoon and Kim, 2011). However, it is uncertain now whether these topic algorithms could be more powerful to distinguish the topics difference which might affect the link generation.…”

SAO-Based Semantic Mining of Patents for Semi-Automatic Construction of a Customer Job Map

“…A Job Map represents the steps for a customer to use a product or service; the customer follows those behaviors in the form [action-object] (AO). This representation form is similar to using a [subject-action-object] (SAO) structure form in theory of solving inventive problem (Transliterated Russian acronym TRIZ) and in the function analysis research fields for abstraction of key concepts [12,13]. The SAO analysis is a method of abstracting and expressing SAO-type structure to effectively organize and express various and large amounts of document data [14,15].…”

“…The SAO analysis is a method of abstracting and expressing SAO-type structure to effectively organize and express various and large amounts of document data [14,15]. The SAO structure is also appropriate for representing contents in a document from a functional view [13,16,17]. Recently, many studies have used text mining techniques for automated content analysis and product design [13,[18][19][20].…”

“…The SAO structure is also appropriate for representing contents in a document from a functional view [13,16,17]. Recently, many studies have used text mining techniques for automated content analysis and product design [13,[18][19][20]. The use of the SAO structure is advantageous in text mining for analyzing massive amounts of technological document data or web data, and has been adopted in various studies such as trend analysis, technology analytics, and patent analysis.…”