Related Research Articles
Information retrieval (IR) is the activity of obtaining information system resources that are relevant to an information need from a collection of those resources. Searches can be based on full-text or other content-based indexing. Information retrieval is the science of searching for information in a document, searching for documents themselves, and also searching for the metadata that describes data, and for databases of texts, images or sounds.
In information science and information retrieval, relevance denotes how well a retrieved document or set of documents meets the information need of the user. Relevance may include concerns such as timeliness, authority or novelty of the result.
The Text REtrieval Conference (TREC) is an ongoing series of workshops focusing on a list of different information retrieval (IR) research areas, or tracks. It is co-sponsored by the National Institute of Standards and Technology (NIST) and the Intelligence Advanced Research Projects Activity, and began in 1992 as part of the TIPSTER Text program. Its purpose is to support and encourage research within the information retrieval community by providing the infrastructure necessary for large-scale evaluation of text retrieval methodologies and to increase the speed of lab-to-product transfer of technology.
The Gerard Salton Award is presented by the Association for Computing Machinery (ACM) Special Interest Group on Information Retrieval (SIGIR) every three years to an individual who has made "significant, sustained and continuing contributions to research in information retrieval". SIGIR also co-sponsors the Vannevar Bush Award, for the best paper at the Joint Conference on Digital Libraries.
Michael S. Lew is a scientist in multimedia information search and retrieval at Leiden University, Netherlands. He has published over a dozen books and 150 scientific articles in the areas of content based image retrieval, computer vision, and deep learning. Notably, he had the most cited paper in the ACM Transactions on Multimedia, one of the top 10 most cited articles in the history of the ACM SIGMM, and the most cited article from the ACM International Conference on Multimedia Information Retrieval in 2008 and also in 2010. He was the opening keynote speaker for the 9th International Conference on Visual Information Systems, the Editor-in-Chief of the International Journal of Multimedia Information Retrieval (Springer), the co-founder of influential conferences such as the International Conference on Image and Video Retrieval, and the IEEE Workshop on Human Computer Interaction. He was also a founding member of the international advisory committee for the TRECVID video retrieval evaluation project, chair of the steering committee for the ACM International Conference on Multimedia Retrieval and a member of the ACM SIGMM Executive Committee. In addition, his work on convolutional fusion networks in deep learning won the best paper award at the 23rd International Conference on Multimedia Modeling. His work is frequently cited in both scientific and popular news sources.
Alan F. Smeaton MRIA is a researcher and academic at Dublin City University. Among his accomplishments are founding TRECVid, the Centre for Digital Video Processing, and being a winner of the University President's Research Award in Science and Engineering in 2002 and the DCU Educational Trust Leadership Award in 2009. Smeaton is a founding director of the Insight Centre for Data Analytics at Dublin City University (2013-2019). Prior to that he was a Principal Investigator and Deputy Director of CLARITY: Centre for Sensor Web Technologies, (2008-2013). As of 2013, Smeaton also serves on the editorial boards for the ACM Journal on Computers and Cultural Heritage, Information Processing and Management and the journal Foundations and Trends in Information Retrieval. Smeaton was elected a Member of the Royal Irish Academy, the highest academic distinction in Ireland, in May 2013, becoming DCU's 10th member. In 2012 Smeaton was appointed by Minister Sean Sherlock to the board of the Irish Research Council
The TREC Genomics track was a workshop held under the auspices of NIST for the purpose of evaluating systems for information retrieval and related technologies in the genomics domain. The TREC Genomics track took place annually from 2003 to 2007, with some modifications to the task set every year; tasks included information retrieval, document classification, GeneRIF prediction, and question answering.
TREC may refer to:
Query expansion (QE) is the process of reformulating a given query to improve retrieval performance in information retrieval operations, particularly in the context of query understanding. In the context of search engines, query expansion involves evaluating a user's input and expanding the search query to match additional documents. Query expansion involves techniques such as:
The Large-Scale Concept Ontology for Multimedia project was a series of workshops held from April 2004 to September 2006 for the purpose of defining a standard formal vocabulary for the annotation and retrieval of video.
Terrier IR Platform is a modular open source software for the rapid development of large-scale Information Retrieval applications. Terrier was developed by members of the Information Retrieval Research Group, Department of Computing Science, at the University of Glasgow.
Human-computer information retrieval (HCIR) is the study and engineering of information retrieval techniques that bring human intelligence into the search process. It combines the fields of human-computer interaction (HCI) and information retrieval (IR) and creates systems that improve search by taking into account the human context, or through a multi-step search process that provides the opportunity for human feedback.
A concept search is an automated information retrieval method that is used to search electronically stored unstructured text for information that is conceptually similar to the information provided in a search query. In other words, the ideas expressed in the information retrieved in response to a concept search query are relevant to the ideas contained in the text of the query.
The Cranfield experiments were computer information retrieval experiments conducted by Cyril W. Cleverdon at the College of Aeronautics at Cranfield in the 1960s, to evaluate the efficiency of indexing systems.
The Fondazione Ugo Bordoni was founded in 1952 and named after engineering professor Ugo Bordoni of the University of Rome. The Foundation supports scientific research and applications of telecommunications and information technology.
Lucene Geographic and Temporal (LGTE) is an information retrieval tool developed at Technical University of Lisbon which can be used as a search engine or as evaluation system for information retrieval techniques for research purposes. The first implementation powered by LGTE was the search engine of DIGMAP, a project co-funded by the community programme eContentplus between 2006 and 2008, which was aimed to provide services available on the web over old digitized maps from a group of partners over Europe including several National Libraries.
The Conference and Labs of the Evaluation Forum, or CLEF, is an organization promoting research in multilingual information access. Its specific functions are to maintain an underlying framework for testing information retrieval systems and to create repositories of data for researchers to use in developing comparable standards. The organization holds a conference every September in Europe since a first constituting workshop in 2000. From 1997 to 1999, TREC, the similar evaluation conference organised annually in the USA, included a track for the evaluation of Cross-Language IR for European languages. This track was coordinated jointly by NIST and by a group of European volunteers that grew over the years. At the end of 1999, a decision by some of the participants was made to transfer the activity to Europe and set it up independently. The aim was to expand coverage to a larger number of languages and to focus on a wider range of issues, including monolingual system evaluation for languages other than English. Over the years, CLEF has been supported by a number of various EU funded projects and initiatives.
Video browsing, also known as exploratory video search, is the interactive process of skimming through video content in order to satisfy some information need or to interactively check if the video content is relevant. While originally proposed to help users inspecting a single video through visual thumbnails, modern video browsing tools enable users to quickly find desired information in a video archive by iterative human–computer interaction through an exploratory search approach. Many of these tools presume a smart user that wants features to interactively inspect video content as well as automatic content filtering features. For that purpose, several video interaction features are usually provided, such as sophisticated navigation in video or search by a content-based query. Video browsing tools often build on lower-level video content analysis, such as shot transition detection, keyframe extraction, semantic concept detection, and create a structured content overview of the video file or video archive. Furthermore, they usually provide sophisticated navigation features, such as advanced timelines, visual seeker bars or a list of selected thumbnails, as well as means for content querying. Examples of content queries are shot filtering through visual concepts, through some specific characteristics, through user-provided sketches, or through content-based similarity search.
Shih-Fu Chang is a Taiwanese computer scientist and electrical engineer noted for his research on multimedia information retrieval, computer vision, machine learning, and signal processing. He is currently the senior executive vice dean of the School of Engineering and Applied Science of Columbia University, where he is also the Richard Dicker Professor. He served as the chair of the Special Interest Group of Multimedia (SIGMM) of Association of Computing Machinery (ACM) from 2013 to 2017. He was ranked as the Most Influential Scholar in the field of Multimedia by Aminer in 2016. He was elected as an ACM Fellow in 2017.
Ellen Marie Voorhees is an American computer scientist known for her work in document retrieval, information retrieval, and natural language processing. She works in the retrieval group at the National Institute of Standards and Technology (NIST).
References
Smeaton, A. F., Over, P., and Kraaij, W. 2006. "Evaluation campaigns and TRECVid". In Proceedings of the 8th ACM International Workshop on Multimedia Information Retrieval (Santa Barbara, California, USA, October 26–27, 2006). MIR '06. ACM Press, New York, NY, 321-330.
