## 5 Conclusions and Future Work  
We have presented a novel technique ICRT to conduct issue-based clustering of scholarly articles, which is essential for the analysis and exploration of highly related research findings in scientific literature. The issue-based article clustering is challenging, as it is difficult to identify the research issues to cluster the articles, and ICRT tackles the challenge by employing the titles of the references cited by scholarly articles, based on the idea that an article often discusses critical issues by citing related references whose titles may indicate the issues. ICRT works as a post-processor to improve various kinds of clustering systems in issue-based clustering. Experimental results show that ICRT \begin{table}
\begin{tabular}{l c c c c c} \hline \hline \multirow{2}{*}{**Article**} & \multicolumn{5}{c}{**Associated Entities (Curated by CTD)**} \\ \cline{2-5}  & **TER** & **DC** & **DKC1** & **IPF** \\ \hline (1) 12785587 (Teomerase & & & & & \\ reverse-transcriptase homozygous & & & & & \\ mutations in autosomal recessive & \(\surd\) & \(\surd\) & \(\surd\) & \(\surd\) & & I in Figure 7) is not identified for this article. \\ [PERSON] syndrome & & & & & \\ \hline (2) 17460043 (Adult-onset pulmonary & & & & & \\ fibrosis caused by mutations in telomerase) & \(\surd\) & & & & \\  & & & & & \\ \hline (3) 23583980 (Genome-wide association & & & & & _OK-TA_: \textless{}TERT, DC\textgreater{} (Target cluster \\ study identifies multiple susceptibility & \(\surd\) & & & & \(\surd\) \\ loci for pulmonary fibrosis) & & & & & \\  & & & & & \\ \hline (4) 22299032 (Zebrafish models for & & & & & \\ dyskeratosis congenita reveal critical & & & & & \\ roles of p53 activation contributing to & \(\surd\) & \(\surd\) & & & \\ hematopoietic defects through RNA & & & & & \\ processing) & & & & & (2) Group this article into \textless{}TERT, & \\  & & & & & & \\  & & & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Errors made by the systems in the case study (see the main text for explanation). successfully improves several systems in identifying clusters of articles with the same research focuses on specific entity associations judged by domain experts. The results are of technical significance. The issue-based clustering task calls for effective overlapping clustering techniques, as target clusters may overlap extremely with each other in practice (ref. the clusters about entity associations curated by CTD in the experiment). ICRT is the first technique to identify main research issues in each scholarly article, and based on the identified issues, conduct overlapping clustering for the articles. The contribution is of practical significance as well, as the clustering of scholarly articles based on research issues can support timely and comprehensive analysis of highly related articles in scientific literature. Scientists often strive to routinely analyze specific issues published in literature (e.g., many scientific evidence databases, such as CTD, GHR, and OMIM, are devoting much effort to routinely updating their databases with focuses on specific research issues, ref. Section 1). It's quite hard for these scientists to conduct timely and comprehensive analyses of highly related articles that focus on the same research issues, because (1) the analysis of even a research issue needs to be based on careful survey of articles in the ever-growing body of scientific literature, and moreover, (2) it is hard to know how research issues are published in the literature. ICRT should thus be integrated with existing article search engines and clustering systems so that the integrated system can conduct article retrieval and issue-based clustering to support the analysis task of the scientists. It is interesting to extend ICRT to provide additional information about the identified clusters, including (1) descriptive terms to label each cluster, and (2) representative articles for each cluster to indicate related articles of the cluster.