@article{zhang2006, title = {{Mining search engine query logs for query recommendation}}, author = {Z. Zhang and O. Nasraoui}, journal = {Proceedings of the 15th international conference on World Wide Web}, pages = {1039--1040}, publisher = {ACM Press New York, NY, USA}, year = 2006, biburl = {http://www.bibsonomy.org/bibtex/2f4873abd71cd109213b349c554cb376d/wnpxrz}, keywords = {log recommendersystems search recommendation query ir} } @inproceedings{243216, title = {Reexamining the cluster hypothesis: scatter/gather on retrieval results}, address = {New York, NY, USA}, author = {Marti A. Hearst and Jan O. Pedersen}, booktitle = {SIGIR '96: Proceedings of the 19th annual international ACM SIGIR conference on Research and development in information retrieval}, pages = {76--84}, publisher = {ACM}, year = 1996, url = {http://portal.acm.org/citation.cfm?id=243216}, location = {Zurich, Switzerland}, isbn = {0-89791-792-8}, doi = {http://doi.acm.org/10.1145/243199.243216}, description = {Reexamining the cluster hypothesis}, biburl = {http://www.bibsonomy.org/bibtex/29b5a5794e780defff1de777633e97a1b/wnpxrz}, keywords = {scatter gather search ir imported clustering} } @inproceedings{citeulike:2045619, title = {Improving Tag-Clouds as Visual Information Retrieval Interfaces}, author = {Y. Hassan-Montero and V. Herrero-Solana}, booktitle = {InScit2006: International Conference on Multidisciplinary Information Sciences and Technologies}, year = 2006, url = {http://nosolousabilidad.com/hassan/improving_tagclouds.pdf}, id = {2045619}, priority = {0}, comment = {proposes using k-clustering and some sort of semantic sorting to refactor tag cloud layout to improve browsing. Not clear on how they actually do it.}, description = {CiteULike: Improving Tag-Clouds as Visual Information Retrieval Interfaces}, abstract = {Tagging-based systems enable users to categorize web resources by means of tags (freely chosen keywords), in order to re-finding these resources later. Tagging is implicitly also a social indexing process, since users share their tags and resources, constructing a social tag index, so-called folksonomy. At the same time of tagging-based system, has been popularised an interface model for visual information retrieval known as Tag-Cloud. In this model, the most frequently used tags are displayed in alphabetical order. This paper presents a novel approach to Tag-Cloud’s tags selection, and proposes the use of clustering algorithms for visual layout, with the aim of improve browsing experience. The results suggest that presented approach reduces the semantic density of tag set, and improves the visual consistency of Tag-Cloud layout.}, biburl = {http://www.bibsonomy.org/bibtex/206f68f9fe46dc6d0f646d932e428dec9/wnpxrz}, keywords = {proj:et proj:bk tagging visualization tag ir cloid} } @inproceedings{strohmaier2007a, title = {How Do Users Express Goals on the Web? - An Exploration of Intentional Structures in Web Search}, author = {M. Strohmaier and M. Lux and M. Granitzer and P. Scheir and S. Liaskos and E. Yu}, booktitle = {We Know'07 International Workshop on Collaborative Knowledge Management for Web Information Systems, in conjunction with WISE'07, Nancy, France}, year = 2007, biburl = {http://www.bibsonomy.org/bibtex/28cafb30efce0f039e1978a7a277f59fa/wnpxrz}, keywords = {goal web search intentional ir user} } @inproceedings{1183747, title = {Information retrieval from relational databases using semantic queries}, address = {New York, NY, USA}, author = {Anand Ranganathan and Zhen Liu}, booktitle = {CIKM '06: Proceedings of the 15th ACM international conference on Information and knowledge management}, pages = {820--821}, publisher = {ACM}, year = 2006, url = {http://portal.acm.org/citation.cfm?id=1183747}, location = {Arlington, Virginia, USA}, isbn = {1-59593-433-2}, doi = {http://doi.acm.org/10.1145/1183614.1183747}, description = {Information retrieval from relational databases using semantic queries}, abstract = {Relational databases are widely used today as a mechanism for providing access to structured data. They, however, are not suitable for typical information finding tasks of end users. There is often a semantic gap between the queries users want to express and the queries that can be answered by the database. In this paper, we propose a system that bridges this semantic gap using domain knowledge contained in ontologies. Our system extends relational databases with the ability to answer semantic queries that are represented in SPARQL, an emerging Semantic Web query language. Users express their queries in SPARQL, based on a semantic model of the data, and they get back semantically relevant results. We define different categories of results that are semantically relevant to the users' query and show how our system retrieves these results. We evaluate the performance of our system on sample relational databases, using a combination of standard and custom ontologies.}, biburl = {http://www.bibsonomy.org/bibtex/2fb055e8b44a99ce23b3d491556c2ec72/wnpxrz}, keywords = {query imported ir semantic} } @article{1011437, title = {Just-in-time information retrieval agents}, address = {Riverton, NJ, USA}, author = {B. J. Rhodes and P. Maes}, journal = {IBM Syst. J.}, number = {3-4}, pages = {685--704}, publisher = {IBM Corp.}, volume = 39, year = 2000, url = {http://portal.acm.org/citation.cfm?id=1011416.1011437}, issn = {0018-8670}, description = {Just-in-time information retrieval agents}, abstract = {A just-in-time information retrieval agent (JITIR agent) is software that proactively retrieves and presents information based on a person's local context in an easily accessible yet nonintrusive manner. This paper describes three implemented JITIR agents: the Remembrance Agent, Margin Notes, and Jimminy. Theory and design lessons learned from these implementations are presented, drawing from behavioral psychology, information retrieval, and interface design. They are followed by evaluations and experimental results. The key lesson is that users of JITIR agents are not merely more efficient at retrieving information, but actually retrieve and use more information than they would with traditional search engines.}, biburl = {http://www.bibsonomy.org/bibtex/2e6b063285a51f88aa566d08a0a693416/wnpxrz}, keywords = {ir imported agent proj:et} } @article{939980, title = {Using Physical Context for Just-in-Time Information Retrieval}, address = {Washington, DC, USA}, author = {Bradley Rhodes}, journal = {IEEE Trans. Comput.}, number = 8, pages = {1011--1014}, publisher = {IEEE Computer Society}, volume = 52, year = 2003, url = {http://portal.acm.org/citation.cfm?id=939980}, issn = {0018-9340}, doi = {http://dx.doi.org/10.1109/TC.2003.1223636}, description = {Using Physical Context for Just-in-Time Information Retrieval}, abstract = {Abstract¿Jimminy is a wearable personal note-taking and note-archival application that automatically displays notes that might be relevant to the wearer in his current environment. The system selects old notes to show on a head-up display based on the wearer's current location, people in the immediate area, and the subject-line and contents of any current notes being written. This paper describes an experiment that evaluates the usefulness of the wearer's physical context (location and people in the area) for automatically finding useful archived information. The results suggest that, while physical context can be used to discover useful archived notes, the subject and text of notes currently being entered are a much better indicator of usefulness in the personal note-taking domain.}, biburl = {http://www.bibsonomy.org/bibtex/2bec14e95a1815cbe05c19912d0ab03c6/wnpxrz}, keywords = {imported ir physical context proj:et} } @inproceedings{Pageetal98, title = {The PageRank citation ranking: Bringing order to the Web}, address = {Brisbane, Australia}, author = {L. Page and S. Brin and R. Motwani and T. Winograd}, booktitle = {Proceedings of the 7th International World Wide Web Conference}, pages = {161--172}, year = 1998, url = {citeseer.nj.nec.com/page98pagerank.html}, biburl = {http://www.bibsonomy.org/bibtex/2ac49c33e114ca171db40cece6a0ae4d6/wnpxrz}, keywords = {pagerank search ranking ir} } @inproceedings{conf/www/RichardsonPB06, title = {Beyond PageRank: machine learning for static ranking.}, author = {Matthew Richardson and Amit Prakash and Eric Brill}, booktitle = {WWW}, crossref = {conf/www/2006}, editor = {Les Carr and David De Roure and Arun Iyengar and Carole A. Goble and Michael Dahlin}, pages = {707-715}, publisher = {ACM}, year = 2006, url = {http://dblp.uni-trier.de/db/conf/www/www2006.html#RichardsonPB06}, ee = {http://doi.acm.org/10.1145/1135777.1135881}, isbn = {1-59593-323-9}, date = {2006-07-17}, description = {dblp}, biburl = {http://www.bibsonomy.org/bibtex/24d2ddff0f0013f7d6cffc782c5eca56c/wnpxrz}, keywords = {search machinelearning ir ranking} } @article{LPage1998, title = {{T}he {A}natomy of a {L}arge-{S}cale {H}ypertextual {W}eb {S}earch {E}ngine}, author = {Sergey Brin and Lawrence Page}, journal = {Computer Networks and ISDN Systems}, month = {April}, number = {1-7}, pages = {107--117}, volume = 30, year = 1998, doi = {10.1016/S0169-7552(98)00110-X}, biburl = {http://www.bibsonomy.org/bibtex/2fc936cec60b1b7ab69f230f14139e8ab/wnpxrz}, keywords = {web ir search} } @techreport{berry94using, title = {Using Linear Algebra for Intelligent Information Retrieval}, author = {Michael W. Berry and Susan T. Dumais and Gavin W. O'Brien}, number = {UT-CS-94-270}, year = 1994, url = {citeseer.ist.psu.edu/berry95using.html}, description = {Using Linear Algebra for Intelligent Information Retrieval - Berry, Dumais, O'Brien (ResearchIndex)}, biburl = {http://www.bibsonomy.org/bibtex/2bcaa7d0ba815e0f2796616c5504fbeff/wnpxrz}, keywords = {svd ir imported} } @misc{gauch-ontologybased, title = {Ontology-Based User Profiles for Search and Browsing}, author = {Susan Gauch and Jason Chaffee and Alexander Pretschner}, year = 2002, url = {citeseer.ist.psu.edu/gauch02ontologybased.html}, description = {Ontology-Based User Profiles for Search and Browsing (ResearchIndex)}, biburl = {http://www.bibsonomy.org/bibtex/27e876459e3a889402eba7dbbe3595b46/wnpxrz}, keywords = {search user imported profile ir ontology browsing} } @inproceedings{Lin:1992, title = {Visualization for the document space}, author = {X. Lin}, booktitle = {Visualization, 1992. Visualization '92, Proceedings., IEEE Conference on}, pages = {274-281}, year = 1992, url = {http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=235198}, isbn = {0-8186-2897-9}, doi = {10.1109/VISUAL.1992.235198}, description = {Welcome to IEEE Xplore 2.0: Visualization for the document space}, abstract = {An information retrieval frame work that promotes graphical displays, and that will make documents in the computer visualizable to the searcher, is described. As examples of such graphical displays, two simulation results of using a Kohonen feature map to generate map displays for information retrieval are presented and discussed. The map displays are a mapping from a high-dimensional document space to a two-dimensional space. They show document relationships by various visual cues, such as dots, links, clusters, and areas, as well as their measurement and spatial arrangement. Using the map displays as an interface for document retrieval systems, the user is provided with richer visual information to support browsing and searching}, biburl = {http://www.bibsonomy.org/bibtex/29a65a0b0bfdf2e6f1682b860a5c28536/wnpxrz}, keywords = {imported ir visualization} } @article{citeulike:488614, title = {Democratic indexing: An approach to the retrieval of fiction.}, author = {Rob Hidderley and Pauline Rafferty}, journal = {Information Services \& Use}, number = {2/3}, pages = {101--109}, volume = 17, year = 1997, id = {488614}, priority = {4}, description = {CiteULike: Democratic indexing: An approach to the retrieval of fiction.}, abstract = {This paper builds on work begun in the field of image indexing [5,7] and examines how an analytical framework to describe the contents of images may be extended to deal with time based materials like film and music. The indexing approach is then considered in relation to fiction. Our project evolved from an analysis of problems related to image retrieval and of solutions currently available [4]. A "levels of meanings" table has been developed by the authors and is being used as an "indexing template" for image retrieval purposes. An image database offers an opportunity to test the image retrieval innovations in a pilot study. Central to the project is the development of the concept of democratic indexing [6]. The authors argue that this concept could be used in many types of information retrieval. Democratic or user based indexing is intended for use in a dynamic retrieval system which would allow users to contribute to the indexing and retrieval process. By focusing on user interpretation, democratic indexing differs from traditional IR models which assume that retrieval mechanisms are constructed by the librarian/indexer. User groups might include newspaper journalists or researchers, but it is clear that the users would have to have something significant to gain from using the system. Users would need to feel that it is worthwhile to contribute as well as to receive. Our approach to image or pictorial information retrieval has incorporated a number of novel features: - the information which is to be recorded for each image includes descriptive cataloguing and subject indexing based on user perceptions of the image and objects within the image [4]; - the collection of user generated indexes will be used to compile a "public" index through a process which we have called "reconciliation"; and - the ability of individual users to record their private indexes offers a "democratic" approach to indexing.}, biburl = {http://www.bibsonomy.org/bibtex/2f41351659d622e45883d0ea7ac3d6b4f/wnpxrz}, keywords = {indexing ir fiction} } @inproceedings{988764, title = {Adaptive web search based on user profile constructed without any effort from users}, address = {New York, NY, USA}, author = {Kazunari Sugiyama and Kenji Hatano and Masatoshi Yoshikawa}, booktitle = {WWW '04: Proceedings of the 13th international conference on World Wide Web}, pages = {675--684}, publisher = {ACM Press}, year = 2004, url = {http://portal.acm.org/citation.cfm?id=988672.988764}, location = {New York, NY, USA}, isbn = {1-58113-844-X}, doi = {http://doi.acm.org/10.1145/988672.988764}, description = {Adaptive web search based on user profile constructed without any effort from users}, abstract = {Web search engines help users find useful information on the World Wide Web (WWW). However, when the same query is submitted by different users, typical search engines return the same result regardless of who submitted the query. Generally, each user has different information needs for his/her query. Therefore, the search result should be adapted to users with different information needs. In this paper, we first propose several approaches to adapting search results according to each user's need for relevant information without any user effort, and then verify the effectiveness of our proposed approaches. Experimental results show that search systems that adapt to each user's preferences can be achieved by constructing user profiles based on modified collaborative filtering with detailed analysis of user's browsing history in one day.}, biburl = {http://www.bibsonomy.org/bibtex/23db95ec7dc4631629b638eb0230cc55a/wnpxrz}, keywords = {web ir user profile imported profiling adaptive search} } @misc{camacho01flexible, title = {Flexible Integration of Planning and Information Gathering}, address = {Toledo (Spain)}, author = {D. Camacho and D. Borrajo and J. Molina and R. Aler}, booktitle = {European Conference on Planning ({ECP}-01)}, month = {September}, pages = {73--84}, publisher = {Springer-Verlag}, year = 2001, url = {citeseer.ist.psu.edu/camacho01flexible.html}, description = {Flexible Integration of Planning and Information Gathering - Camacho, Borrajo, Molina, Aler (ResearchIndex)}, biburl = {http://www.bibsonomy.org/bibtex/2d8919c72ea82428f2076012eb1623c51/wnpxrz}, keywords = {imported planning ir web} } @inproceedings{1288560, title = {Blog search and mining in the business domain}, address = {New York, NY, USA}, author = {Yun Chen and Flora S. Tsai and Kap Luk Chan}, booktitle = {DDDM '07: Proceedings of the 2007 international workshop on Domain driven data mining}, pages = {55--60}, publisher = {ACM Press}, year = 2007, url = {http://portal.acm.org/citation.cfm?id=1288552.1288560&coll=GUIDE&dl=}, location = {San Jose, California}, isbn = {978-1-59593-846-6}, doi = {http://doi.acm.org/10.1145/1288552.1288560}, description = {Blog search and mining in the business domain}, biburl = {http://www.bibsonomy.org/bibtex/28add5688facb791bda4e6db738eb1654/wnpxrz}, keywords = {ir search mining business blog} } @inproceedings{SheungOnChoy:2006, title = {Web Information Retrieval in Collaborative Tagging Systems}, author = {Sheung-On Choy and A.K. Lui}, booktitle = {Web Intelligence, 2006. WI 2006. IEEE/WIC/ACM International Conference on}, pages = {352-355}, year = 2006, url = {http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=4061393}, isbn = {0-7695-2747-7}, doi = {10.1109/WI.2006.191}, description = {IEEE Xplore# Wrapper Result}, abstract = {Collaborative tagging on the Web has been quickly gaining ground as a new paradigm for Web information retrieval, discovering and filtering. There are a number of successful deployments of collaborative tagging systems that effectively recruits the activity of human users into collecting and annotating vast amounts of Web resources. They lead to an emergent categorization of Web resources in terms of tags, and create a different kind of Web directory. However, the current ways of exploration in the tagging space are limited, which cannot get the most out of the real value of it. This paper presents our methodology, observations, and experimental results in the way we propose how to improve the user experience in exploring information captured by collaborative tagging systems}, biburl = {http://www.bibsonomy.org/bibtex/25ff241f25e900781577bed68ed2cb217/wnpxrz}, keywords = {imported collaborative tagging ir web} } @misc{allan97interactive, title = {Interactive Cluster Visualization for Information Retrieval}, author = {J. Allan and A. Leouski and R. Swan}, year = 1997, url = {citeseer.ist.psu.edu/allan97interactive.html}, description = {Interactive Cluster Visualization for Information Retrieval - Allan, Leouski, Swan (ResearchIndex)}, abstract = {This study investigates the ability of cluster visualization to help a user rapidly identify relevant documents. It provides added support for the truth of the Cluster Hypothesis on retrieved documents and shows that clustering of relevant documents is readily visible. The study then shows the visual effect of a technique similar to relevance feedback and shows how to enhance that effect to further help the user locate relevant material. A ranked list returned by a text search engine purports...}, biburl = {http://www.bibsonomy.org/bibtex/21e812543ac2929cf85e5ee475efe3c36/wnpxrz}, keywords = {ir search proj:et clustering visualization imported} } @article{whittle2006, title = {{Query transformations and their role in Web searching by the general public}}, author = {M. Whittle and B. Eaglestone and N. Ford and V.J. Gillet and A. Madden}, journal = {Information Research}, number = 1, volume = 12, year = 2006, biburl = {http://www.bibsonomy.org/bibtex/2a3a38920006837a63ccfdcd7eda4d3fe/wnpxrz}, keywords = {query web search ir} }