01819nas a2200217   4500008004100000245006000041210006000101260000900161300001400170490000600184520115700190653001801347653001301365653002801378653001601406653001501422100001601437700001601453700001501469856011701484       2010                        eng d00aMining the blogosphere to generate cuisine hotspot maps0 aMining the blogosphere to generate cuisine hotspot maps  c2010  a396 - 4010 v83 aChoosing a restaurant is one of the most frequent decisions faced in modern daily life; however, it is difficult for consumers to choose between food/restaurant by reading large amounts of reviews. This study attempts to generate cuisine hotspot maps through blog content mining to help consumers make restaurant decisions by specialties. The main obstacle in doing this involves recognizing and extracting restaurants and essentialrestaurant information (i.e., restaurant dishes) in unstructured content. In contrast to traditional Named Entity Recognition (NER) targets, dish name is a promising target that received little attention in previous studies. This study develops methods for recognizing and extracting restaurant names and dish names from review postsin the blogosphere and achieves satisfactory performance. Based on the method, we processed more than 12,000 Chinese blog posts and generated a cuisine hotspot map. The map shows the most popular dishes of restaurants in a map-view to help consumers make restaurant decisions. A prototype of cuisine hotspot map, named CuisineGuide, is implemented and available as an iPhone application.10aBlog analysis10aHotspots10aName entity recognition10aWeb content10aWeb search1 aShih, C.-C.1 aPeng, T.-C.1 aLai, W.-S.  uhttp://www.scopus.com/inward/record.url?eid=2-s2.0-79960266928&partnerID=40&md5=4f85ee81adec856534db4c96673f0dbe