Need comment about 2 categories from Low User

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Writing analysis – still

I am writing on analysis of BASIC COMPETENCY USER who employed INSTANT FILER strategy. Working parallel between writing and drawing the model.

– Finished both – will try to fix writings and merge models.

– Then compared between the model of LOW COMPETENCY USER AND BASIC.

-Compared between manegemnt strategy.

Compared between the old model (earlier model) with this 2 models.

Sadly, from 9-15 have to accompany husband and children to entertain his brother and wife who are visiting us for 2 weeks time. Gosh! such a pressure for me. Trying to bring work during travelling.

–Hopefully, end of April be able to have some comparisons, method writings and analysis amendment on writing plus the model plotting.

So less time, but a lot to do……

Why why I would be able to see it before…..

Enough said, push your self harder……

Refer back vs retrieval

I am trying to write about the retrieval process. But  some how got stuck with the word refer back and retrieval.

Are this 2 concepts the same?

Or does somebody do something , to make retrieval easy?

For example:

Located the information (working in the temporary location) to make it easy accessible for duartion of time?

Hmmmm it sounds similar  relation

- in the sense of to be able to access easily without browsing again and again or go to the long way to be able to find some infor again?

Or it need to be retrieve first than refer again (for a duration of time)—hmmm seems logical.

- retrieval:

1) Link 1

C.J. van Rijsbergen

B.Sc., Dip. NAAC, Ph.D., F.B.C.S., F.I.E.E., C.Eng., F.R.S.E.

Information Retrieval Group
Department of Computing Science
University of Glasgow
Glasgow G12 8QQ
SCOTLAND

keith@dcs.gla.ac.uk

Link 2

he Information Retrieval paradigm is about a person (human or physical) having a need for information, and a set of information objects from which this need is to be satisfied. In this chapter we provide general models to formalize the concept of information need.

A searcher has a need for certain information. This need may have both qualitative and quantitative aspects. In the context of an information collection, the searcher tries to formulate this need in terms of this collection, translating the need for information into a need for information objects (documents). The starting point of our discussion will be a searcher having a need for documents in the collection.

The information collection may be a stable (fixed) collection, in which case an Information Retrieval System may preprocess the collection for optimal disclosure. The intention of this preprocessing is that the Information Retrieval System gets an impression of the contents of each document. This calls for a contents description mechanism.

The collection may be a (continuous) stream of documents (like a newsgroup on the Internet). For each next document, the Information Retrieval System has to decide if it will be interesting for the searcher. This is referred to as the Information Filtering paradigm. In this case there can be no preprocessing of all documents. Descibing document contents then is either based on some universal system for contents description, or the system should try to build such a system incrementally when new documents arrive. This is also the situtation on the world wide web, an extremely large, dynamic and volatile collection of documents.

A difference between Information Retrieval and Information Filtering is that a searcher interest is valid during some period of time, while a query only expresses the information need at some point in time. As there may be content fluctuations in the document stream, there may also be fluctuation in the searcher interest.

Information retrieval is a wide, often loosely-defined term but in these pages I shall be concerned only with automatic information retrieval systems. Automatic as opposed to manual and information as opposed to data or fact. Unfortunately the word information can be very misleading. In the context of information retrieval (IR), information, in the technical meaning given in Shannon’s theory of communication, is not readily measured (Shannon and Weaver[1]). In fact, in many cases one can adequately describe the kind of retrieval by simply substituting ‘document’ for ‘information’. Nevertheless, ‘information retrieval’ has become accepted as a description of the kind of work published by Cleverdon, Salton, Sparck Jones, Lancaster and others. A perfectly straightforward definition along these lines is given by Lancaster[2]: ‘Information retrieval is the term conventionally, though somewhat inaccurately, applied to the type of activity discussed in this volume. An information retrieval system does not inform (i.e. change the knowledge of) the user on the subject of his inquiry. It merely informs on the existence (or non-existence) and whereabouts of documents relating to his request.’ This specifically excludes Question-Answering systems as typified by Winograd[3] and those described by Minsky[4]]. It also excludes data retrieval systems such as used by, say, the stock exchange for on-line quotations.

To make clear the difference between data retrieval (DR) and information retrieval (IR), I have listed in Table 1.1 some of the distinguishing properties of data and information retrieval. One may want to criticise this dichotomy on the grounds that the boundary

that in IR we are searching for relevant documents as opposed to exactly matching items. The extent of the match in IR is assumed to indicate the likelihood of the relevance of that item. One simple consequence of this difference is that DR is more sensitive to error in the sense that, an error in matching will not retrieve the wanted item which implies a total failure of the system. In IR small errors in matching generally do not affect performance of the system significantly.

In dilema – have several ideas – to proceed

However, manage to get all the LOW COMPETENCY user open categories.

Having said that, I am in the dilema and have several solutions or testing for it:

1) either start with LC users with axial coding, applied paradigm model and propose it (theoretical sampling].

2) proceed with coding (recording dialectic) with basic competency user and high level user – meaning still in the open coding process.

3) or it seems could be done parallel.

4) How to generate theory/proposition base on the data? A problem for me….

Links to theory creation

1) Alan Dix

pdf version

2) Research methodolog in this book – bought it.