1. LIS510 lecture 3 Thomas Krichel 2005-02-05

2. information storage & retrieval this area is now more know as information retrieval when I dealt with it I meant storage as including the organization of the information, which is a bit of a stretch Ideally, one needs to know the retrieval needs before designing the organization of the information

3. information retrieval has to do with anything of how the user gets to the information out of an information system. it is different from data retrieval since the retrieved data has to be “relevant” to the user. it is very difficult to say what “relevance” is, objectively.

4. information retrieval performance how was it for you? the traditional methods are –precision = number of relevant documents retrieved divided by total number of retrieved documents –recall = number of relevant documents retrieved divided by total number of relevant document. they only evaluate a search!

5. information retrieval models they give formal account of the search process. there are three basic flavor –Boolean information retrieval –Vector information retrieval –Probabilistic information retrieval All are mathematical model I would also add web information retrieval as a new type

6. web information retrieval this has become big business now find a user’s need is a way to connect them with advertising. One way that has made Google such a success is that they discovered a way to make appear quality web sites to the top Basically, a quality web site is one that has many links to it from other quality sites.

7. information storage can mean the preparation of information before searching –which fields are searchable –can there be a variety of means to rank searches? –is there use of a controlled vocabulary difficult to make general conclusions but to say that advanced search features are not much used.

8. human-computer interface tries to understand how users work with computer systems the idea is to build “user-friendly” systems but don’t leave that to a “computer designer” as suggested by Rubin note that information systems go way beyond computers. Web usability is a big topic.

9. natural language processing Rubin classifies this as a part of computer- human interface natural language processing is still in its infancy speech recognition is the best developed part others are working on connecting computers to the brain

10. artificial intelligence This has been around for a while. The field has developed a number of theoretical tools Some of them are being used in practice now. Things like RDF, the Resource Description Framework, are based on artificial intelligence theory. It is a tool to aggregate knowledge from web resource.

11. Area 3: defining information & its value There is debate on the nature of –data (Thomas: things that can be processed in the information system) –knowledge (Thomas: stuff that is in people’s head) –information (something between data and knowledge). Rubin says its meaning given to data. Rubin also talks about wisdom as “knowledge applied for the benefit of humanity”

12. scientific view of information usually information is modeled as something that reduces uncertainty people have a rough idea about something, say tomorrow’s temperature the information is the fact that this something will actually take a precise value, when we know what the temperature is or when we have less uncertainty. usually this uses probability theory.

13. value of information economists can value information precisely but their definition is useless for practical purposes much of the work then involves some cost/benefit analysis. in such analysis one can reach almost any result one wants.

14. elements of value-added in libraries access to resources accuracy (for example of bibliographic data) browsing (like in library stacks) currency (things are up-to-date) flexibility (through human interaction) formatting (laying out the collection, signs) interfacing (probably close to flexibility) ordering (buy access to things) access to means to get to resources

15. area 4: bibliometrics is the application of quantitative methods to the study of information resources Mainly concerned with the structure of the resources. The typical example is citation analysis. Quantitative Studies of use fall more to the first area of interest.

16. bibliometric laws Zipf’s law related to the usage of terms in text. Lotka’s law related to the number of papers written by authors. Bradford’s law relates to the distribution of articles in a field across a number of periodicals.

17. citation analysis is the heart of bibliometrics. Two important concept –bibliographic coupling means two documents share some reference –co-citation means two documents are cited by the same documents Citation analysis is also important for scientific activity evaluation

18. area 5: management & admin This is an expanding area in libraries. Rather than collecting physical books, libraries have to negotiate on-line access. Area covers all of information policy. Example problems are –copyright –censorship Measuring performance is part of user studies

19. area 6: information architecture art and science of organizing information and its interfaces so that seekers find what they want quickly mainly used with respect to large web sites. it looks at the contents rather than technical factors or the look-and-feel A related idea is usability

20. area 7: knowledge management this comes from the business environment it is a management fad that has overstayed its welcome.

21. http://openlib.org/home/krichel Thank you for your attention!