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space and their maintenance may be very time-consuming, because in many
cases the inverted indexes have to be regenerated. this is why the expressions
of an inverted list are reduced to those terms which have been collected in a
controlled vocabulary.
Boolean retrieval has some weaknesses. In particular, the quality of a retrieval
result is very dificult to control. furthermore, in some cases the retrieval
is considered to be too strict. A request such as A ∧ B ∧ C delivers results
only if the data contains all three expressions; the result is empty if only
two conditions are fulilled.
Vector model
In general, vector model-based systems lead to the best result in retrieval
processes. Instead of focusing on single-index items from a microscopic point
of view, the vector model starts from a macroscopic perspective. It supposes
that documents are characterised by the statistical distribution of the terms.
when a retrieval is started, a vector model-based system tries to identify those
documents which suit the query best with regard to the statistics of the concerned
terms. to do so, formulae have been developed which help to calculate
the similarity between various documents.
the calculation of distances between text documents is based on high dimensional
vectors of features. the features identiied in all documents of a
given collection are extracted. the sum of all these features creates a feature
space. On the basis of predeined selection criteria, the number of these features
is reduced. the elimination of so-called stop words is one of a number of
applied techniques. Another one determines — by means of statistical analysis
— particularly high or low frequent terms. At the end of this phase, which
is generally called feature reduction, the feature space has n dimensions.
It is now possible to describe each text of the collection by a vector. the
value of an element in each dimension, v j , is deined by the feature matrix
which corresponds to the document. the concrete value of v j depends on the
applied methodology. Sometimes it is suficient to signal the presence or absence
of a feature by the igures 0 and 1. In other cases, the absolute of normalised
frequence is preferred. Normalisation is generally necessary to compensate
for the varying length of documents. the distance between two texts can
now be determined on the basis of the corresponding vectors. Simple values
depend on the distance between the points deined by the vectors in an
n-dimensional space or by the angle which is formed by the vectors. In general,
the values are normalised to results which are placed between 0 and 1, for
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