The user of the library of the future need not be a person. It may be another knowledge system, that is, any intelligent agent with a need for knowledge. - Edward Feigenbaum

SIMILE: "a joint project conducted by the MIT Libraries and MIT Computer Science and Artificial Intelligence Laboratory. SIMILE seeks to enhance inter-operability among digital assets, schemata / vocabularies / ontologies, metadata, and services. A key challenge is that the collections which must inter-operate are often distributed across individual, community, and institutional stores. We seek to be able to provide end-user services by drawing upon the assets, schemata/vocabularies/ontologies, and metadata held in such stores."

The Digital Access Architect. By Vanessa Neblett, Cassandra Shivers, Nils Thingvall and Bobby Tsui. Library Journal (November 1, 2005). "This July, the Digital Archive Architects at Orange County Library System (OCLS) in Orlando, FL, offered patrons two ways to access a program on how to plan a wedding using the Internet. Patrons flocked to the Wedding Virtual Gallery but shunned the trek to the library for similar material. The online option got 205 page views in one month; one person showed up for the face-to-face program. It's the job of the new Digital Access Architects (DAA) to address how to change the one-on-one model of providing information into a one-to-many dissemination of information in order to serve increasing and increasingly niched populations. ... Currently we are working to develop an easy reference tool using an artificial intelligence called a chatterbot. It allows patrons to ask questions in natural language rather than doing a keyword search or drilling down through categories to find answers to their questions. ... Trying to create a virtual librarian is no small task. Experimenting with several different solutions involves delving into artificial intelligence markup language (AIML), which is used to program the bot and interpret user questions."

iVia: High Octane Software for Internet portal and Virtual Library Creation and Management. "The iVia system is an INFOMINE creation generously funded by the National Science Digital Library of the National Science Foundation, the National Leadership Grant Program of the U.S. Institute of Museum and Library Services, the Fund for the Improvement of Post-Secondary Education of the U.S. Department of Education and the Library of the University of California, Riverside." As explained on the New Technologies page:

• "A number of machine learning based text and information processing technologies, developed over the last five to ten years in the computer sciences, are beginning to deliver useful advancements in automatically or semi-automatically detecting, extracting, organizing and providing good access to Internet delivered information.
• "iVia utilizes a range of programs known as crawlers to traverse the Web and identify new Internet resources. iVia's crawlers are used to help identify important academic resources on the Internet. The crawlers function as .collection development. tools."
• "iVia, as mentioned, supports fully expert created metadata, fully automatically created metadata, and metadata that is automatically created and then expert refined and augmented (i.e., semi-automatically created). ... These automated extraction and classifier programs are part of a suite of programs known as the 'Record Builder'."

Using Machine Learning to Support Quality Judgments. By Myra Custard and Tamara Sumner. D-Lib Magazine (October 2005; Volume 11, Number). "Our long-term research objective is to use state-of-the-art methodologies in machine learning and natural language processing to develop a computational model of quality that approximates expert human judgments. Developing a computational model of quality that approximates expert judgments is a foundational requirement for developing interfaces and tools that can optimize and scaffold the complex human decision processes and procedures associated with collection curation. If the dimensions of quality can be effectively modeled and represented, we can envision a suite of future intelligent collection curation tools based on this underlying computational model including:* Tools that support library accessioning staff in making more consistent choices with respect to resource quality;* Tools that support library accessioning staff in quickly and reliably identifying potentially problematic resources that may not reflect the desired quality standards specified in library policies;* Tools that support review teams to engage in strategically targeted reviewing."

New system solves the 'who is J. Smith' puzzle. Penn State Live (December 14, 2006). "Penn State researchers have developed an automated system that can determine which 'J. Smith' is authoring papers on computer science -- the one who teaches at Penn State or the one who teaches at M.I.T -- as well as whether 'J. Smith' is John Smith, Jane Smith, Joanna L. Smith or James H. Smith. ... 'The system works by using machine-learning methods to cluster together names that the system believes to be similar. If you think there’s another parameter that's relevant, you can change the algorithm and include it,' [ C. Lee] Giles said. The system is explained in a paper, 'Efficient Name Disambiguation for Large-Scale Databases,' presented at the recent 17th European Conference on Machine Learning and the 10th European Conference on Principles and Practice of Knowledge Discovery in Databases in Berlin. ... The algorithm will be a part of the next generation CiteSeer, the largest academic search engine for computer and information-science literature. Giles was co-creator of CiteSeer when he was at NEC."

• This paper, as well as others such as "Automatic categorization of figures in scientific documents," (presented at the Joint Conference on Digital Libraries 2006), are available from C. Lee Giles' publications collection.

XLibris: An Automated Library Research Assistant. By Larry Birnbaum, Jay Budzik, Andrew Crossen, Kristian Hammond, and Mason Warner (Northwestern University InfoLab).In Proceedings of the 2001 International Conference on Intelligent User Interfaces, ACM Press. "The XLibris system automatically retrieves, aggregates, and delivers information about books to users as they are checked out of the library, using information about the books themselves and the user’s task. XLibris locates books in the Dewey Decimal subject hierarchy to automatically search for the most relevant information about the book for the user, tailoring both the sources queried and the information returned based on the book’s position in the hierarchy."

Artificial Intelligence and Libraries...a primer for librarians. Laura Zick's 1999 project at the School of Library and Information Science, Indiana University. "We in the library community understand that enormous changes are at hand in our field. We are evolving from centralized, physical paper-based archives into distributed networks of quality digital knowledge. We strive to seamlessly and proactively deliver mission-critical information to the point of need; no longer bound by four walls, the library can act as a gateway to the world's knowledge. In order to achieve this grand and plausible vision, we must free ourselves from some of the more mundane tasks of our field: artificial intelligence techniques can provide us with this freedom."

The Work of Information Mediators: A Comparison of Librarians and Intelligent Software Agents. By Laura Zick. First Monday, Volume 5, Number 5 (May 2000). "In this paper, the author examines the characteristics of information agency, the work of librarians and of intelligent agents as information mediators, the differences between human and software agents, the possible tasks for software agents in libraries, and speculates on the future of human and software agency. A typical medical library-based information need is presented and the attendant information processes are examined. The author describes the future of information mediation as based on efficient interaction between human and software agents and provides examples of possible collaborative information tasks."

Google's Moon Shot - The quest for the universal library. By Jeffrey Toobin. The New Yorker (February 5, 2007). "Google’s is not the only book-scanning venture. Amazon has digitized hundreds of thousands of the books it sells, and allows users to search the texts; Carnegie Mellon is hosting a project called the Universal Library, which so far has scanned nearly a million and a half books; the Open Content Alliance, a consortium that includes Microsoft, Yahoo, and several major libraries, is also scanning thousands of books; and there are many smaller projects in various stages of development. Still, only Google has embarked on a project of a scale commensurate with its corporate philosophy: 'to organize the world’s information and make it universally accessible and useful.' ... The story of how Brin and Google’s other co-founder, Larry Page, met as graduate students in computer science at Stanford in the mid-nineties, and devised a series of elegant software algorithms that allowed Web searchers to find relevant information quickly and efficiently, has become part of Silicon Valley lore. Less well known is that, at the time, Brin and Page were also working on Stanford’s Digital Library Technologies Project, an attempt, funded by the federal government, to organize different kinds of stored information, including books, articles, and journals, in digital form. 'There was an attitude in computer science that putting things on dead trees was obsolete and getting it all into a searchable, digital format was a quest that had to be accomplished someday,' Terry Winograd, a Stanford professor who was a mentor to Page and Brin, said. ... The chief engineer of Google’s system for scanning books in the library collections is Dan Clancy, who joined the company after eight years at NASA, where he supervised teams of Ph.D.s. working on problems related to artificial intelligence. ... Copying all those pages presents many difficulties, but writing software to make the books useful to searchers is even harder. 'The scanning technology is boring,' Clancy said. 'The real challenge is to get somebody something that they are actually interested in, inside a book.'"

The Infinite Library. By Wade Roush. Technology Review (May 2005). "The digitization of the world’s enormous store of library books -- an effort dating to the early 1990s in the United Kingdom, the United States, and elsewhere -- has been a slow, expensive, and underfunded process. But last December librarians received a pleasant shock. Search-engine giant Google announced ambitious plans to expand its 'Google Print' service by converting the full text of millions of library books into searchable Web pages. At the time of the announcement, Google had already signed up five partners, including the libraries at Oxford, Harvard, Stanford, and the University of Michigan, along with the New York Public Library. More are sure to follow. Most librarians and archivists are ecstatic about the announcement, saying it will likely be remembered as the moment in history when society finally got serious about making knowledge ubiquitous.... ([Susan] Wojcicki’s example shows how history can, indeed, come full circle. Google founders Larry Page and Sergey Brin developed BackRub, the predecessor to the Google search engine, while working on an early library digitization project at Stanford that was funded in part by the National Science Foundation’s Digital Libraries Initiative. And PageRank, Google’s core search algorithm, which orders sites in search results based on the number of other sites that link to them, is simply a computer scientist’s version of citation analysis, long used to rate the influence of articles in scholarly print journals)."

the nora project: "The goal of the nora project is to produce software for discovering, visualizing, and exploring significant patterns across large collections of full-text humanities resources in existing digital libraries. In search-and-retrieval, we bring specific queries to collections of text and get back (more or less useful) answers to those queries; by contrast, the goal of data-mining (including text-mining) is to produce new knowledge by exposing unanticipated similarities or differences, clustering or dispersal, co-occurrence and trends. Over the last decade, many millions of dollars have been invested in creating digital library collections: at this point, terabytes of full-text humanities resources are publicly available on the web. Those collections, dispersed across many different institutions, are large enough and rich enough to provide an excellent opportunity for text-mining, and we believe that web-based text-mining tools will make those collections significantly more useful, more informative, and more rewarding for research and teaching. In this effort, we will build on data-mining expertise at the University of Illinois' Graduate School of Library and Information Science and on several years of software development work that has been done at the University of Illinois' National Center for Supercomputing Applications (NCSA), developing the D2K (Data to Knowledge) software, in Michael Welge's Automated Learning Group."

Debabelizing Libraries - Machine Translation by and for Digital Collections. By David A. Smith. D-Lib Magazine (March 2006; Volume 12, Number 3). "Just as translation builds libraries, libraries nurture translation. Machine translation, even in embryo, provides some hope that ever expanding digital collections can also greatly expand their audience. That hope derives, in part, from the ways that massive digital libraries can enrich and change research on machine translation. Works in digital (and print) collections are translated at unequal rates. A small number of works -- in religious and literary canons -- are translated again and again. A moderate number are translated once or a few times, and the great mass are never translated at all. This Zipfian distribution (with its 'long tail') provides a mutual opportunity for MT and digital libraries: at the peak, MT can benefit from massively parallel translations; in the middle, MT can help DLs find and align existing translations; in the tails, MT can provide readers with finding and browsing aids for multilingual texts (Figure 1). I will first ground these predictions in the origins and development of data-driven, or empirical, machine translation (MT). I then describe some major subproblems in MT research and note how they might adapt to benefit, or benefit from, emerging comprehensive digital libraries. Finally, we see how MT and digital libraries could enter a virtuous cycle of collection, augmentation, and access. ... The generation of Second World War code breakers Turing, von Neumann, Shannon, and Wiener invented computing machinery and, almost simultaneously, the idea of translation as mechanized 'decoding'. Hopes for easily ingesting Russian technical literature receded into the future until the Automatic Language Processing Advisory Committee (ALPAC) report of 1966 recommended that the U.S. government stop funding machine translation."

What I Learned This Week. By Joseph Janes, American Libraries Columnist. American Libraries Online. (April 2005). "Monday: Clifford Lynch, demigod of the information world, nominally executive director of the Coalition for Networked Information, but more appropriately known as that incredibly smart guy who travels the world searching out the novel, cool, and important and weaves them together into thoughtful ruminations. ... My favorite sentence? 'We are only now getting over the assumption that we write articles to be read by other people.' If you want your writing to be widely found, it has to go through an increasing number of computational processes, including spidering, indexing, data mining, and machine translation; and new generations of such beasts are constantly under development. ... Friday: Oren Etzioni, from the University of Washington computer science department, spoke on the future of web searching. His was a far more technical talk (and one which drew noticeably far fewer librarians), plunging me deep into my background in information retrieval. His first sentence was easy enough to understand: Web searching is moving from document-retrieval to question-answering, because that’s what people really want. ... There’s a great deal of interesting work here, from probabilistic information-retrieval (straight out of information science, by the way) to artificial intelligence. ... Quite a week. I’m still processing it all, but I’ll tell you this: I’m glad I’m part of a profession that embraces and fosters change and complexity. As the nature of documents and their use evolves, and technology enables increasingly sophisticated manipulation and creation of them, a profession that clung stubbornly to tradition for tradition’s sake would be in a world of hurt . . . but that’s another story."

Making books readable on computer proves trying task. By Michelle Kessler. USA Today (December 15, 2004). "It's not very easy to teach a computer to read. Turning paper books into searchable digital files requires artificial intelligence. It's tough for computers to pick up on visual clues that humans use when they read a book. Think about it: In many type fonts, the number '1' and lower-case letter 'l' are identical. How can a computer figure out the difference? Scientists have worked on the problem for more than 20 years. They're making big strides, but the results are imperfect. ... Special software, called optical character recognition (OCR), allows computers to look at a picture and pick out words. ... Carnegie Mellon University's 'Million Book Project' aims to put a million books online in partnership with 18 universities in India and China. Although the project will promote the schools' libraries, it's mainly a research problem for its computer science department, says Gloriana St. Clair, Carnegie Mellon's dean of libraries."

Robots get bookish in libraries. By Jo Twist. BBC News (July 21, 2004). "Robots have disappointed humans so far in their ability to mix and help people in their everyday lives. Other than industry and research, they have mostly been for entertainment. But a group of robotics researchers at University Jaume I in Spain is working on a robot librarian which could deliver the promise of a helpful bot. The prototype has cameras, sensors and grippers so it can locate and collect a book. The hope is that one day teams of service robots could work in libraries. ... Because the database will only give an approximate location, the robot will navigate its way to the bookshelf, using its infrared and laser guidance system, and scan books within a four-metre radius. 'Once it is in there, it starts using its cameras. By moving the arm with the cameras, it takes an image of the bookshelf,' said Professor [Angel del] Pobil. 'It can read the labels and the position of the book using its image processing and optical character recognition software,' the professor said."

Physics/Astronomy "Virtual Libraries" Join Forces to Offer Powerful, New Personalized Web and E-mail Alerts. Press release from the Harvard-Smithsonian Center for Astrophysics (April 18, 2005). "'The capabilities of myADS are unique and rather powerful,' said Guenther Eichhorn (CfA), ADS project scientist. 'We use advanced AI [artificial intelligence] techniques to deliver exactly the information that scientists want and need.' According to [Michael] Kurtz and Eichhorn, ADS uses complex statistical evaluations of use patterns and of article reference lists to help select the most interesting and significant recent literature for a given search request. When combined with the state-of-the-art AI techniques used by myADS, these search techniques offer a fast and highly effective method to find papers that are most important to an individual scientist. 'It's the best thing since two pieces of sliced bread were assembled to make a sandwich,' said Paul Ginsparg, Professor of Physics and Information Science at Cornell University."

In Remote Library Stacks, an All-Seeing, Scanning Robot. By Yudhijit Bhattacharjee. The New York Times; June 27, 2002 (registration req'd). "In libraries of the future, researchers at Johns Hopkins University say, that kind of grunt work could be handled by robotic systems linked to the Internet. As the first step toward building such a system, the researchers have designed a robot that can move about inside a library and locate a book requested by a user, take it off the shelf and carry it to a nearby scanning station. In the system's envisaged final version, a second robot at the scanning station would scan specific pages of the book that the user was interested in. The user would then be able to leaf through the book over the Internet from any location. ... Robots are already being used in a handful of libraries around the world ... A robotic system manufactured by ABB, a Finnish automation company, and installed at a municipal library in Vaasa, Finland, takes items dropped off by users out of a bin and sorts them by subject."

• Also see:
  • The Evelyn Wood of Digitized Book Scanners. By John Markoff. The New York Times (May 12, 2003; no fee reg. req'd.). "Putting the world's most advanced scholarly and scientific knowledge on the Internet has been a long-held ambition for Michael Keller, head librarian at Stanford University. But achieving this goal means digitizing the texts of millions of books, journals and magazines -- a slow process that involves turning each page, flattening it and scanning the words into a computer database. Mr. Keller, however, has recently added a tool to his crusade. On a recent afternoon, he unlocked an unmarked door in the basement of the Stanford library to demonstrate the newest agent in the march toward digitization. Inside the room a Swiss-designed robot about the size of a sport utility vehicle was rapidly turning the pages of an old book and scanning the text. The machine can turn the pages of both small and large books as well as bound newspaper volumes and scan at speeds of more than 1,000 pages an hour. Occasionally the robot will stumble, turning more than a single page. When that happens, the machine will pause briefly and send out a puff of compressed air to separate the sticking pages."

Data-Mining. California Computer News (October 27, 2004). "The Andrew W. Mellon Foundation is funding the two-year, nearly $600,000 multi-institutional project, which John Unsworth, dean of Illinois' Graduate School of Library and Information Science (GSLIS), will lead. In his winning project, titled 'Web-based Text-Mining and Visualization for Humanities Digital Libraries,' Unsworth expects to produce software 'for discovering, visualizing and exploring significant patterns across large collections of full-text humanities resources in digital libraries and collections.' ... In traditional 'search-and-retrieval' projects, scholars bring specific queries to collections of text and get back more or less useful answers to those queries, Unsworth said. 'By contrast, the goal of data-mining, including text-mining, is to produce new knowledge by exposing unanticipated similarities or differences, clustering or dispersal, co-occurrence and trends.'"

Knowledge Processing -- From File Servers to Knowledge Servers. By Edward Feigenbaum. A chapter from The Age of Intelligent Machines by Raymond Kurzweil (1990). "Now imagine the library as an active, intelligent knowledge server. It stores the knowledge of the disciplines in complex knowledge structures (perhaps in a knowledge-representation formalism yet to be invented). It can reason with this knowledge to satisfy the needs of its users. These needs are expressed naturally, with fluid discourse. The system can, of course, retrieve and exhibit (i.e., it can act as an electronic textbook). It can collect relevant information; it can summarize; it can pursue relationships. It acts as a consultant on specific problems, offering advice on particular solutions, justifying those solutions with citations or with a fabric of general reasoning. If the user can suggest a solution or a hypothesis, it can check this and even suggest extensions. Or it can critique the user viewpoint with a detailed rationale of its agreement or disagreement. It pursues relational paths of associations to suggest to the user previously unseen connections. Collaborating with the user, it uses its processes of association and analogizing to brainstorm for remote or novel concepts. More autonomously, but with some guidance from the user, it uses criteria of being interesting to discover new concepts, methods, theories, and measurements. The user of the library of the future need not be a person. It may be another knowledge system, that is, any intelligent agent with a need for knowledge."

"The Informedia Digital Video Library project is a research initiative at Carnegie Mellon University funded by the NSF, DARPA, NASA and others that studies how multimedia digital libraries can be established and used. The Informedia project has pioneered new approaches for automated video and audio indexing, navigation, visualization, search and retrieval and embedded them in a system for use in education, information and entertainment environments. Intelligent, automatic mechanisms are being developed to populate the library. Research in the areas of speech recognition, image understanding, and natural language processing supports the automatic preparation of diverse media for full-content and knowledge based search and retrieval."

Is Conservation Ready for Artificial Intelligence? Bonnie Rose Curtin. Abbey Newsletter. Volume 14, Number 1 (February 1990). Discusses the expert system GRASP (Guide and Resources for Archival Strategic Preservation Planning).

Turning The Page - E-books will have a more profound effect on librarians than the invention of the printing press. By Doug Johnson. School Library Journal (November 2004; page 44 - subscription required). "The librarian's expertise, available online and accessible through e-books, will still be the single most valuable resource the library has to offer. We'll need to possess not only the expertise to locate specific materials, resources, and information, but the know-how to use expert systems that rely on artificial intelligence to answer our patrons' tough questions."

Application of Expert Agents/Assistants in Library and Information Systems. By James G. Williams and Ken Sochats, Department of Information Science and Telecommunications, University of Pittsburgh (1997). Abstract: "This article will present a brief overview of expert agents and assistants and then discuss activities in several areas of library and information centers where expert systems have been developed and where intelligent agents/assistants could be of practical use in such activities. A discussion of what an intelligent agent or assistant might perform in these areas is outlined."

Libraries and expert systems. Edited by Craig McDonald and John Weckert. 1991. "The application of expert systems to libraries had developed steadily during recent years, and is an area of significant innovation in the provision of library and information services. The papers from a major international meeting on expert systems and libraries, hosted by Charles Sturt University and attended by some 250 participants are published together in the present volume."

• Collaborative Filtering (@ Filtering)
• Customer Relations
• Information Retrieval & Extraction

Bush, Vannevar. 1945. As We May Think. The Atlantic Monthly. 176: 101-108.