PLIDMiner: A Quality Based Approach for Researcher's Homepage Discovery

摘要

Researchers' high quality homepages are important resources in academic search because they provide comprehensive and up-to-date information about researchers. Meanwhile, low quality homepages widely exist. A case study shows that 57.8% of all homepages retrieved among top 10 results from Google are low quality and 95% top researchers own out-of-date homepages. Besides, some academic portals generate dynamic homepages introducing researchers. These homepages are not maintained by researchers and may contain incorrect information. The quality of discovered homepages can not be ensured by existing work, which decreases the efficiency of academic search. It is difficult to define a high quality homepage from a quantitative perspective. Instead, on the basis of analyzing labeled high quality homepages, we propose "informative researcher's homepage", at least consisting of identifiable information (introducing a researcher's basic information) and publication list (listing his/her corresponding publications), as an estimation for high quality homepage. Based on the observation that informative researchers' homepages are organized in two ways, integrated and scattered, we propose an effective discovering model, PLIDMiner, with F1 scores over 0.9 on labeled data. Our model can also be applied to verify homepages' quality. We crawl thousands of homepage resources from popular academic portals and assess their overall qualities. It turns out that nearly 25% of homepage resources in these portals are not informative, which strengthens our motivation.