The paper discusses a very specific problem in information retrieval (IR) communities, namely, how to improve patent recognition by incorporating content such as drawings and sketches with particular emphasis on flowchart diagrams.

The architecture and approach resembles the well-known content-based image retrieval (CBIR), with the intention of addressing CBIR’s semantic gap, which occurs between queries between similar images. This is, at least, the impression given in the introduction.

In actuality, the authors discuss an approach and architecture, which mostly focus on flowchart structural similarities rather than semantic ones. Furthermore, they mostly discuss how the two alternative branches, pixel-based (raster) and vectorial (vector graphics) representations compare with each other. The experiments and evaluation based on datasets from the CLEF-IP 2012 campaign does strengthen this viewpoint in that the flowchart recognition procedure is claimed to be improved.

In this context, the architecture, approach, and similarity measurement hardly address the semantics in the contents of the flowchart, unless the transcriptions (text labels on flowchart nodes and edges) are meant to be considered as the semantics of flowcharts. In any case, it is not clear whether the intended patent search system will be capable of comparing and detecting similarities holding among flowcharts, which may have a slightly different structure. If so, it is also not clear whether further aspects such as degrees of similarities or similarities holding among integral parts of flowcharts will be provided.

Therefore, the paper is primarily intended for an audience of researchers in information retrieval with an emphasis on CBIR, with the content being a mixture of text and image or purely image (drawings, sketches, other). It is also for developers of patent search systems, as well as those working in patent offices.