@inproceedings{niwa2006web,
  abstract = {There have been many attempts to construct web page recommender systems using collaborative filtering. But the domains these systems can cover are very restricted because it is very difficult to assemble user preference data to web pages, and the number of web pages on the Internet is too large. In this paper, we propose the way to construct a new type of web page recommender system covering all over the Internet, by using Folksonomy and Social Bookmark which are getting very popular in these days.},
  author = {Niwa, Satoshi and Doi, Takuo and Honiden, Shinichi},
  booktitle = {Proceedings of the Third International Conference on Information Technology: New Generations (TNG'06)},
  interhash = {380f4bafa6f23f100225c700561e2e80},
  intrahash = {3ff65017f9ad0085950d26bf10134df2},
  lastdatemodified = {2006-12-04},
  lastname = {Niwa},
  own = {notown},
  pages = {388-393},
  read = {notread},
  title = {Web Page Recommender System based on Folksonomy Mining for ITNG �06 Submissions},
  url = {http://doi.ieeecomputersociety.org/10.1109/ITNG.2006.140},
  year = 2006
}

@article{mller2004textpresso,
  abstract = {We have developed Textpresso, a new text-mining system for scientific literature whose capabilities go far beyond those of a simple keyword search engine. Textpresso's two major elements are a collection of the full text of scientific articles split into individual sentences, and the implementation of categories of terms for which a database of articles and individual sentences can be searched. The categories are classes of biological concepts (e.g., gene, allele, cell or cell group, phenotype, etc.) and classes that relate two objects (e.g., association, regulation, etc.) or describe one (e.g., biological process, etc.). Together they form a catalog of types of objects and concepts called an ontology. After this ontology is populated with terms, the whole corpus of articles and abstracts is marked up to identify terms of these categories. The current ontology comprises 33 categories of terms. A search engine enables the user to search for one or a combination of these tags and/or keywords within a sentence or document, and as the ontology allows word meaning to be queried, it is possible to formulate semantic queries. Full text access increases recall of biological data types from 45% to 95%. Extraction of particular biological facts, such as gene-gene interactions, can be accelerated significantly by ontologies, with Textpresso automatically performing nearly as well as expert curators to identify sentences; in searches for two uniquely named genes and an interaction term, the ontology confers a 3-fold increase of search efficiency. Textpresso currently focuses on Caenorhabditis elegans literature, with 3,800 full text articles and 16,000 abstracts. The lexicon of the ontology contains 14,500 entries, each of which includes all versions of a specific word or phrase, and it includes all categories of the Gene Ontology database. Textpresso is a useful curation tool, as well as search engine for researchers, and can readily be extended to other organism-specific corpora of text. Textpresso can be accessed at http://www.textpresso.org or via WormBase at http://www.wormbase.org.},
  author = {M�ller, Hans-Michael and Kenny, Eimear E. and Sternberg, Paul W.},
  interhash = {da91fb436b69ed009eeff34378b1ccbe},
  intrahash = {430a15f443153c0e37b37b55eb60b3a8},
  journal = {PLoS Biology},
  lastdatemodified = {2006-12-04},
  lastname = {M�ller},
  number = 11,
  own = {notown},
  pages = 309,
  pdf = {mueller04-textpresso.1371_journal.pbio.0020309-S.pdf},
  read = {notread},
  title = {Textpresso: An Ontology-Based Information Retrieval and Extraction System for Biological Literature},
  url = {http://dx.doi.org/10.1371%2Fjournal.pbio.0020309},
  volume = 2,
  year = 2004
}

@article{doms2005gopubmed,
  abstract = {The biomedical literature grows at a tremendous rate and PubMed comprises already over 15 000 000 abstracts. Finding relevant literature is an important and difficult problem. We introduce GoPubMed, a web server which allows users to explore PubMed search results with the Gene Ontology (GO), a hierarchically structured vocabulary for molecular biology. GoPubMed provides the following benefits: first, it gives an overview of the literature abstracts by categorizing abstracts according to the GO and thus allowing users to quickly navigate through the abstracts by category. Second, it automatically shows general ontology terms related to the original query, which often do not even appear directly in the abstract. Third, it enables users to verify its classification because GO terms are highlighted in the abstracts and as each term is labelled with an accuracy percentage. Fourth, exploring PubMed abstracts with GoPubMed is useful as it shows definitions of GO terms without the need for further look up. GoPubMed is online at www.gopubmed.org. Querying is currently limited to 100 papers per query.},
  author = {Doms, Andreas and Schroeder, Michael},
  file = {doms2005gopubmed.pdf:doms2005gopubmed.pdf:PDF},
  interhash = {ede77029ab0af6a88de781cda6b15d6b},
  intrahash = {ba0b96d0895f18d41b4c8f0614b1bc72},
  journal = {Nucleic Acids Res},
  lastdatemodified = {2006-12-04},
  lastname = {Doms},
  month = Jul,
  number = {Web Server issue},
  own = {notown},
  pages = {783--786},
  pdf = {doms05-gopubmed.pdf},
  read = {notread},
  title = {{{G}o{P}ub{M}ed: exploring {P}ub{M}ed with the {G}ene {O}ntology}},
  url = {http://dx.doi.org/10.1093/nar/gki470},
  volume = 33,
  year = 2005
}

@article{bernerslee2001semantic,
  author = {Berners-Lee, Tim and Hendler, James and Lassila, Ora},
  interhash = {e87f09446138a81e6478625da97885b6},
  intrahash = {222934145a71a9d6cfbbb375d4d62c1d},
  journal = {Scientific American},
  lastdatemodified = {2007-04-27},
  lastname = {Berners-Lee},
  month = May,
  number = 5,
  own = {notown},
  pages = {34-43},
  read = {notread},
  title = {The Semantic Web},
  url = {http://www.sciam.com/article.cfm?articleID=00048144-10D2-1C70-84A9809EC588EF21},
  volume = 284,
  year = 2001
}