Community Detection and Growth Potential Prediction Using the Stochastic Block Model and the Long Short-term Memory from Patent Citation Networks

Scoring patent documents is very useful for technology management. However, conventional methods are based on static models and, thus, do not reflect the growth potential of the technology cluster of the patent. Because even if the cluster of a patent has no hope of growing, we recognize the patent is important if PageRank or other ranking score is high. Therefore, there arises a necessity of developing citation network clustering and prediction of future citations. In our research, clustering of patent citation networks by Stochastic Block Model was done with the aim of enabling corporate managers and investors to evaluate the scale and life cycle of technology. As a result, we confirmed nested SBM is appropriate for graph clustering of patent citation networks. Also, a high MAPE value was obtained and the direction accuracy achieved a value greater than 50% when predicting growth potential for each cluster by using LSTM.Comment: arXiv admin note: substantial text overlap with arXiv:1904.1204

Community Detection and Growth Potential Prediction from Patent Citation Networks

The scoring of patents is useful for technology management analysis. Therefore, a necessity of developing citation network clustering and prediction of future citations for practical patent scoring arises. In this paper, we propose a community detection method using the Node2vec. And in order to analyze growth potential we compare three ''time series analysis methods'', the Long Short-Term Memory (LSTM), ARIMA model, and Hawkes Process. The results of our experiments, we could find common technical points from those clusters by Node2vec. Furthermore, we found that the prediction accuracy of the ARIMA model was higher than that of other models.Comment: arXiv admin note: text overlap with arXiv:1607.00653 by other author

Anisakis (Filocapsularia) type幼線虫による肉芽腫の一例

We encoutered a patient suspected of appendicitis. and after the surgical operation we discovered four migrated worms in the submucous tissue of the small intestine. These worms, from their morphology and fine structures of the body, were proven to be larvae of Amsakis (Filocapsularia) type Nematoda

Association of Constitutive Hyperphosphorylation of Hsf1p with a Defective Ethanol Stress Response in Saccharomyces cerevisiae Sake Yeast Strains

Modern sake yeast strains, which produce high concentrations of ethanol, are unexpectedly sensitive to environmental stress during sake brewing. To reveal the underlying mechanism, we investigated a well-characterized yeast stress response mediated by a heat shock element (HSE) and heat shock transcription factor Hsf1p in Saccharomyces cerevisiae sake yeast. The HSE-lacZ activity of sake yeast during sake fermentation and under acute ethanol stress was severely impaired compared to that of laboratory yeast. Moreover, the Hsf1p of modern sake yeast was highly and constitutively hyperphosphorylated, irrespective of the extracellular stress. Since HSF1 allele replacement did not significantly affect the HSE-mediated ethanol stress response or Hsf1p phosphorylation patterns in either sake or laboratory yeast, the regulatory machinery of Hsf1p is presumed to function differently between these types of yeast. To identify phosphatases whose loss affected the control of Hsf1p, we screened a series of phosphatase gene deletion mutants in a laboratory strain background. Among the 29 mutants, a Δppt1 mutant exhibited constitutive hyperphosphorylation of Hsf1p, similarly to the modern sake yeast strains, which lack the entire PPT1 gene locus. We confirmed that the expression of laboratory yeast-derived functional PPT1 recovered the HSE-mediated stress response of sake yeast. In addition, deletion of PPT1 in laboratory yeast resulted in enhanced fermentation ability. Taken together, these data demonstrate that hyperphosphorylation of Hsf1p caused by loss of the PPT1 gene at least partly accounts for the defective stress response and high ethanol productivity of modern sake yeast strains