# Emerging Perspectives of Blockchains in Food Supply Chain Traceability Based on Patent Analysis
## 2 Materials and Methods  
### Review Approach  
Extraction of the patent portfolio from patent databases was performed using the commercial software platform PatSnap [41; 42]. Both active granted patents and pending patent applications were extracted. Patent title, abstract, and body text were searched using the following terms: ((blockchain OR \"block chain\" OR blockchains OR \"block chains\") AND (traceability) AND (\"food supply chain\" OR \"food value chain\" OR \"agri-food chain\" OR \"food supply chains\")). Extracted patent attributes included application number, title, classification code, priority and application date, abstract, family count, legal status, and the number of backward and forward citations (Figure 1). A patent portfolio of 82 documents was created, among which 26% were active patents, 70% were pending patent applications in different phases, and 4% of documents were undetermined. The patent application trends and the application authority structure was analyzed for the created patent portfolio. For the interpretation of the obtained unstructured document collections, topic modelling based on Latent Dirichlet Allocation (LDA) was performed [43]. The documents were parsed prior to data processing. The text in abstracts were pre-processed in the following manner:  
* Removal of punctuations, digits, words, and tags shorter than four characters
* Conversion of letters to lowercase
* Filtering of words not contributing to the meaning of the phrase (stop words)
* Reduction of words to their roots using the Porter stemming algorithm [44]  
The pre-processed abstract texts were used to group patents in the portfolio into technology topics using Latent Dirichlet Allocation modeling (LDA) [45]. In LDA, documents are viewed as random mixtures of different topics, where each topic is characterized according to the distribution of words. The topic distributions in documents share the common Dirichlet prior \(\alpha\), and the word distributions of topics share the common Dirichlet prior \(\eta\). Given the parameters \(\alpha\) and \(\eta\) for document d, parameter \(\theta_{\text{d}}\) of a multinomial distribution over K topics is constructed from Dirichlet distribution \(\theta_{\text{d}\,|\,\alpha}\). Similarly, for topic k, parameter \(\beta_{\text{k}}\) of a multinomial distribution over all words is derived from Dirichlet distribution \(\beta_{\text{k}\,|\,\eta}\). The generative process of the LDA method is given in Table 1.  
Figure 1: Screenshot of an example of a relational table for collected patent documents. ponent classification codes were analyzed, and we proposed titles that best described each topic. We manually classified the most frequent words, identified by LDA as nouns, verbs, adverbs, and other words, to enable understanding of the common features for each topic. The International Patent Classification (IPC) system was used, given it is the most frequently used system to hierarchically organize the structure of technical fields and technological areas of a patent. The patent, depending on the technical broadness of the covered invention, may have several IPC codes assigned to it, and all assigned IPC codes were taken into consideration in the analysis. The outcome of the LDA was used to draw a dynamic picture of the development of BC technologies application in FSCs, with analysis of geographical distribution, and identification of the most valuable patent applications was based on patent forward citations and patent family size [32; 46; 47; 48]. In the cited works, influential patents having dominant technology or high applicability are distinguished and, accordingly, were used as an indicator of a patent's technological significance. A simple patent family representing a set of patents applied in various countries to protect a single invention, besides representing the importance of technology, also reveals the width of its potential market [32; 46]. A larger patent family is indicative of the attractiveness of the protected invention or that the technology is more innovative.