The individual search for information about physicians on Web 2.0 platforms can affect almost all aspects of our lives. People can directly access physician rating websites via web browsers or use any search engine to find physician reviews and ratings filtered by location resp. specialty. However, sometimes keyword search does not meet user needs because of the disagreement of users’ common terms queries for symptoms and the widespread medical terminology. In this paper, we present the prototype of a specialised search engine that overcomes this by indexing user-generated content (i.e., review texts) for physician discovery and provides automatic suggestions as well as an appropriate visualisation. On the one hand, we consider the available numeric physician ratings as sorting criterion for the ranking of query results. Furthermore, we extended existing ranking algorithms with respect to domain-specific types and physicians ratings on the other hand. We gathered more than 860; 000 review texts and collected more than 213; 000 physician records. A random test shows that about 19.7% of 5; 100 different words in total are health- related and partly belong to consumer health vocabularies. Our evaluation results show that the query results fit user's particular health issues when seeking for physicians.    «

The individual search for information about physicians on Web 2.0 platforms can affect almost all aspects of our lives. People can directly access physician rating websites via web browsers or use any search engine to find physician reviews and ratings filtered by location resp. specialty. However, sometimes keyword search does not meet user needs because of the disagreement of users’ common terms queries for symptoms and the widespread medical terminology. In this paper, we present the prototyp...    »