ANALYSING TERMS, PAIRS, TRIPLETS AND FULL QUERIES
USED IN INTRANET SEARCHING
Dick Stenmark
IT University of Göteborg, Department of Applied IT, P.O.Box 8718, SE-40275 Göteborg, Sweden
Keywords: Intranet, search engine usage, query term analysis.
Abstract: Web search engines have become often-used tools for many ordinary people today and a growing number of
researcher are therefore studying how these lay-persons interact with such tools. Studies of public web
search engine usage have often produced term frequency lists to illustrate the information needs the users.
This study differs on several aspects from previous work. Firstly, we have analysed the logs of an intranet
search engine, since studies of corporate internal search behaviour are in short supply. Secondly, we have
not just used search terms but also full queries and show that single terms give a skewed understanding.
Thirdly, we have analysed data from three different years - 2000, 2002 and 2004 - to be able to detect shifts
and trends in information seeking behaviour.
1 INTRODUCTION
Intranets, i.e., corporate internal webs, have in less
than 10 years time gone from being perceived as a
spelling error to become one of the most widespread
organisational information technologies, and the
information available on intranets seems to grow at a
higher pace than the web itself (Stenmark, 2005b).
Obviously, organisational members need good
search tools to find the information they need and
since public search engines such as Google are
unable to access and index the content of the
intranets, organisations have to install and host their
own internal search tools.
However, it has been noticed that intranets have
their own specific characteristics and that
information seeking behaviour seen on the public
web not necessarily can be expected to be repeated
on intranets (Fagin et al., 2003). Intranet information
is narrower in the sense that it is business oriented
and more context specific. Intranets provide
important business information environments and to
understand the information need and behaviour of
the organisational members is thus of vital interest
for organisations to be able to provide suitable
resources and for researchers and developers to be
able to design better tools.
In this paper, we contribute to the understanding
of intranet search behaviour by providing a
longitudinal comparison of the queries submitted to
a corporate intranet search engine. Our data covers
three different weeks from the years 2000, 2002, and
2004. In particular, we have studied not only the
most frequently used search terms (which is
otherwise a common approach) but also the actual
queries, including term pair and term triplet. We
have also studied how these have changed over time
and identified both short- and long-term information
needs.
The paper is organised as follows. In the next
section we account for related research from intranet
and public web studies and thereafter we present out
research setting and research method. In section four
the result of or work is accounted for and we
subsequently discuss this in detail in section five. In
section six, finally, we draw our conclusions and
suggest design implications based on our findings.
2 RELATED WORK
Relatively little work has yet been devoted to
intranet searching and practically nothing to the
content of intranet searching. Choo et al. (1998)
studied corporate employees’ use of the web as an
information resource to support their daily work
activities, and found them engage in a range of
complementary modes of information seeking,
122
Stenmark D. (2007).
ANALYSING TERMS, PAIRS, TRIPLETS AND FULL QUERIES USED IN INTRANET SEARCHING.
In Proceedings of the Third International Conference on Web Information Systems and Technologies - Web Interfaces and Applications, pages 122-129
DOI: 10.5220/0001260501220129
Copyright
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 SciTePress

varying from undirected viewing to formal
searching. Göker and He (2000) examined a week’s
worth of log file data from Reuter’s intranet search
engine in order to develop a method for automatic
session boundary detection. Hawking et al. (2000)
implemented a search engine on a university intranet
in order to “reality test” an algorithm, and in a
similar vein, Fagin et al. (2003) studied IBM’s
intranet with a focus on technical matters. Stenmark,
finally, reported a time-based analysis of a week’s
worth of intranet search engine behaviour but he
only studied how users interacted with the
technology; not what they actually searched for
(Stenmark, 2005a). The current study does thus
make an explicit contribution to this field, but it also
means that there is little previous work on which to
build. We have thus had to compare and contrast or
results to what is known about public web searching.
On the public web there are two types of search
engines – general-purpose engines (such as e.g.
Google) and site specific ones (e.g. the one found at
www.ibm.com). The most consistent examination of
public search engine usage has been carried out by
Spink and Jansen, who over the last decade have
established a useful research base of web searching
behaviour (e.g. Jansen et al., 2000; Spink & Jansen,
2004; Spink et al., 2001; 2002). When it comes to
site specific search engines, Chau et al.’s (2005)
analysis of the Utah state web site search engine is a
useful contribution. Such local web site search
engines have much in common with intranet search
engines, we argue, and we shall use the results of
Chau and colleagues as a point of reference for our
own work.
Chau et al. (2005) found both similarities and
differences when comparing general-purpose search
engine users and web site search engine users. The
users in Chau et al.’s study used an average of 2.25
terms per query, which is close to the numbers
reported for public search engines (Silverstein et al.,
1999; Jansen et al., 2000; Spink et al., 2001). The
average number of result pages examined (1.47) is
also fully in line with what has previously been
reported. As far as these aspects were concerned,
there was no difference between the two user
groups. However, the web site search engine users
only submit, in average, 1.25 queries per session,
which is only about half the amount reported for
public search engine users. Chau et al. suggest that
this may be because web site search engine users
have more specific information needs. Further, in the
Utah study almost 30% of all queries were phrase
searches, i.e., contained quotation marks, whereas
Spink & Jansen (2001) only found 5% in their study.
However, the most significant difference was,
not surprisingly, the content of the queries; Chau et
al. compared the most frequently used query terms
with those reported by Spink et al. (2001). Chau and
colleagues found that web site search engine users
submitted terms much more related to the specific
domain. Comparing the top 50 terms from Chau et
al. and Spink et al., only 9 terms occur in both lists
and only two of those are functional words rather
than semantic words. This, again suggests that web
site searchers have a more specific information need
than do users of general-purpose search engines.
In addition, Chau and colleagues also examined
the whole queries and found big differences
compared to the single term lists. However, they did
not present any theory as to why this difference
existed. We shall adopt their approach in our study,
as explained next, and extend Chau et al.’s study in
two ways; firstly by adopting it to the intranet
domain and secondly by providing a multiple-year
analysis in contrast to Chau et al.’s single year study.
3 RESEARCH SETTING &
METHOD
This research is based on analysis of search engine
log files from Jupiter’s intranet. Jupiter (a
pseudonym) is a big Swedish manufacturer group
with offices and production plants in many countries
around the world that employs some +80,000
people. Jupiter’s intranet was established in 1995
and quickly developed into a large information
repository. In 1998, Jupiter purchased and
implemented a commercial search engine, and when
spidering the intranet little over 400,000 documents
were indexed from some 450 web servers. These
numbers continued to grow; at the end of the
millennium the search engine had indexed 750,000
documents and found more than 700 web servers
and in 2002 there were over 1,500 known web
servers on the intranet, according to Jupiter sources.
The search engine generates a log file where
every transaction the users have with the server is
recorded. This log file contains the IP addresses of
the users’ computers, the date and time (datetime) of
the transactions (as logged by the server using
Central European Time), the query strings as entered
by the users, information regarding which result
pages the users have requested, and some additional
parameters not used in this particular study. The
three log files used were collected in 2000, 2002 and
2004, respectively. The 2000 log file contains almost
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123

four week’s worth of transactions from January 31st
to February 24th. The 2002 log file contains one
week’s worth of transactions from October 21st to
October 27th, and the 2004 log file, finally, contains
one week’s worth of transactions from October 14th
to October 20th. In all, the log files contain more
than 128,000 activities from more than 23,000 users.
Transaction log analysis (TLA) is a well-
established method when examining search engine
usage (Jansen, 2006). Still, commentators
acknowledge that no standardised metrics have been
agreed upon and interpretations and definitions
differ between studies (cf. Jansen & Pooch, 2004;
Spink et al., 2001). In our study, we extracted all
query strings from the log files and sorted and
counted all queries. These queries where thereafter
split up in individual words and operators, and
counted for frequency.
We also counted all term pairs and term triplets.
This included both “natural” pairs/triplets where
users explicitly had submitted the two/three terms
together (such as in human resources or Jupiter golf
competition), and “derived” pairs/triplets where
these were extracted from longer query phrases (e.g.,
the query Jupiter golf competition generates the two
pairs Jupiter golf and golf competition). All results
were thereafter analysed and compared to the results
reported by Chau et al. and other related work.
4 RESULTS
We first calculated the absolute frequency for every
query term and year. For year 2000 we found 17,390
different terms (hereafter referred to as types). Of
these types, 10,376 terms or 59.7% were only used
once (hereafter referred to as hapaxes). However,
many types were also repeated resulting in a corpus
of 69,369 search words (hereafter referred to as
tokens) being submitted. For year 2002 we had a
corpus of 25,320 tokens containing 8,021 types
(31.7%). 4,722 or 59.5% of the types were hapaxes.
For year 2004, finally, we had 30,719 tokens
consisting of 9,037 types (29.4%) and 5,179 hapaxes
(57.3%).
The above statistics are summarised in Table 1.
The 100 most frequently used terms (the top-100)
accounted for between 22.9 and 24.0% of the total
terms, as can also be seen in table 1. In addition,
table 1 accounts for the portion of the total that the
top-50 and top-10 terms result in.
Table 1: Basic statistics for this study.
2000 2002 2004
Number of tokens 69,360 25.320 30.719
Number of types 17,390 8.021 9.037
top-100 22.9% 24.0% 23.0%
top-50 16.8% 17.6% 16.0%
top-10 8.0% 7.7% 7.3%
Number of hapaxes 10.377 4.772 5.179
out of total 15.0% 18.8% 16.9%
out of different 59.7% 59.5% 57.3%4
We manually analysed the top-100 search terms
for each year but due to space limitations we only
present the top-25 terms in table 2 below. There
were a total of 185 different types amongst the 300
most frequently used search tokens. Thirty-two of
these (representing 17.3%) were found across all
three years. Another 49 terms (26.5%) were found in
two of the years, and the remaining 104 terms
(56.2%) were only used in one year.
Table 2: The 25 most frequently occurring search terms
for the three years.
pos 2000 2002 2004
1 jupiter jupiter jupiter
2 servicebilar coda coda
3 servicebil outlook rapido
4 and rapido tidinfo
5 coda pc outlook
6 sif standard it
7 standard tidinfo service
8 word mail gps
9 rapido servicebilar ebd
10 it web password
11 job mailforms gdi
12 class parma business
13 service password standard
14 eddo it parts
15 lift service parma
16 ford eddo group
17 quality and web
18 lediga parts tdm
19 competition gps reseräkning
20 jbb forms and
21 products business pbp
22 golf std plan
23 product access gdp
24 mcs class global
25 r70 mcs of
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Looking specifically at the top-10 for each year,
we found the distribution to be very similar. Three
out of a total of 19 types (representing 15.8%) were
amongst the top-10 for all three years (jupiter,
rapido, coda), five terms (26.3%) were found in two
of the years, and 11 terms (57.9%) were only found
in one top-10 set.
The frequencies of the terms appearing in table 2
were left out due to space limitations but to give the
reader a flavour of the numbers we here present a
few samples. Position #1 for the year 2000 (jupiter)
occurred 1,713 times, position #10 (it) 262 times,
position #50 (download) 104 times, and position
#100 (bus) occurred 70 times. Corresponding
frequencies for 2002 were 414, 108, 43, and 27, and
for 2004 655, 120, 51, and 35. As can be seen from
these numbers, the frequencies drop radically with
decreasing rank. This is a since long known
phenomenon documented by Zipf, who noted that a
double-log rank-frequency plot generates a straight
line with a slop of -1 for large (English) texts (Zipf,
1932). Plotting the query words from our log data in
such diagrams, our lines were not as steep as Zipf’s
prediction; the slopes for the three years were
-0.8895, -0.8133, and -0.8435, respectively. Figure 1
shows the plot for the year 2000 data.
Figure 1: Double-log rank-frequency plot showing the
Zipf distribution for the year 2000 (k=-1 indicated).
In contrast to table 2 above, which lists the most
frequently used terms, tables 3 and 4 below show the
most frequent pairs and triplets, respectively, found
amongst the query terms. The tables contain both
naturally occurring pairs and triples and derived
occurrences, i.e., pair and triplets extracted from
longer text sequences. As we can see, the term
jupiter is in tables 3 and 4 combined with other
words and appears in about one third of the
pairs/triplets, and many of the frequent terms in table
2 (such as coda, sif, rapido, and tidinfo) are not
represented in tables 3 and 4.
Table 3: The 10 most frequently occurring query pairs and
their frequencies for the three years.
2000 2002 2004
Pos Freq
Terms
Freq
Terms
Freq
Terms
1 152
golf
competition
51 web access 56 jupiter it
2 131 lediga jobb 43 mail forms 43
jupiter
culture
3 104
jupiter
servicebilar
42 hem pc 27 jupiter lifts
4 96
jupiter
products
40
utbildnings
pc
27 the jupiter
5 81 jupiter it 37 jupiter it 26
jupiter
products
6 80
jupiter
product
34
standard
parts
25
jupiter
group
7 77 jupiter golf 25 jupiter bil 25
function
group
8 63 jupiter lift 23
business
plan
25
outlook
password
9 59 jupiter nu 20
change
password
24
business
plan
10 53
jupiter
culture
19
jupiter
culture
23
business
objects
The tables contain both naturally occurring pairs
and triples and derived occurrences, i.e., pair and
triplets extracted from longer text sequences. As we
can see, the term jupiter is in tables 3 and 4
combined with other words and appears in about one
third of the pairs/triplets, and many of the frequent
terms in table 2 (such as coda, sif, rapido, and
tidinfo) are not represented in tables 3 and 4.
We examined the top 25 term pairs for each year
(Tables 3 and 4 show only the top-10 due to space
limitations). Out of the 75 term pairs, only 4 pairs
(jupiter products, jupiter it, jupiter culture and
business plan) were present in all three years, which
corresponds to 5.3%. Another 11 pairs (14.7%) were
present in two of the years, whereas the remaining
60 pairs (80.0%) only ranked amongst the top-25 in
one year. Comparing tables 2 and 3, we see that
although there are no term pairs in table 2, many of
the terms in table 2 can be seen in the pairs of table
3. Many of the highly ranked pairs consist of terms
on the top-100 list.
When examining the top-25 triplets from each
year we found that only one of the 75 term triplets
(the jupiter culture) was represented in all three
years, which corresponds to 1.3%. Another 4 triplet
(5.3%) were present in two of the years, whereas the
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125

remaining 70 triplets (93.3%) only were present in
one year. Table 4 shows the top-10 triplets.
Table 4: The 10 most frequently occurring query triplets
and their frequencies for the three year.
2000 2002 2004
Pos
Freq
Terms
Freq
Terms
Freq
Terms
1 71
jupiter
golf
competitio
n
13
-jbb -jbt
jlt
20
the jupiter
culture
2 29
word for
windows
7
function
group
index
10
code of
conduct
3 25
2000
1999
1998
7
localizaçã
o das
concessio
nar
10
jupiter lifts
plant
4 24
aftermark
et and
service
6
who is
who
9
jupiter do
brasil
5 23
no 4
1999
6
design
building
landscapi
ng
8
i-shift gear
box
6 23
cst
newsletter
, no
6
the jupiter
culture
8
regulations
and
certification
7 23
newslette
r, no 4
5
outlook
web
access
7
engine
data sheet
8 20
jupiter
servicebil
ar ab
5
jac quality
policy
7
lifts plant
in
9 18
jupiter
action
service
5 -jbt jlt -it 7
welding
manual
design
10 16
jupiter
attitude
survey
5
one
company
vision
6
class for
unix
We also examined the most frequently occurring
queries as submitted by the users and we found that
single term queries dominated; there are only nine
multiple term queries amongst the top-100 for the
year 2000 and eight and seven for the years 2002
and 2004, respectively. There is only one three-term
query (jupiter golf competition) and ten of the
multiple term queries contain the word jupiter (the
top-25 are presented in table 5).
Twenty-five queries (12.6%) were present
amongst the top-100 all three years. Almost half of
these (12) were to (in-house) systems of various
kinds (e.g., coda, rapido, or outlook). Nearly a third
(8) were HR-related or link to employee-specific
matters, and the remaining concerned organisational
matters and miscellaneous. Thirty-nine queries
(19.7%) were amongst the top-100 in two years.
With only 3 exceptions, it was always from two
adjacent years, i.e., 2000-2002 or 2002-2004.
Finally, two thirds of the top-100 words or 134
instances were present in one single year only. These
terms were difficult to classify since the represented
a wide spread of interests.
One noticeable difference when comparing table
2 with table 5 is that the term jupiter has disappeared
from the latter. Comparing the top-100 year by year,
we found only 46 overlapping terms for the year
2000, 56 terms for year 2002, and 39 for year 2004.
Table 5: The 25 most frequently submitted queries for
each year (multiple-word queries coloured).
pos 2000 2002 2004
1
servicebilar coda coda
2
servicebil rapido rapido
3
coda outlook tidinfo
4
sif tidinfo ebd
5
rapido mailforms gps
6
eddo parma parma
7
mcs servicebilar gdi
8
metall eddo tdm
9
word gps pbp
10
standard mcs reseräkning
11
class cats sox
12
parma reseräkning outlook
13
c-bil servicebil impact
14
tdm hempc cats
15
cf webmail gdp
16
blanketter standard teamplace
17
lediga jobb tdm mailforms
18
bilbiten utbildningspc vinst
19
sörredsgården web access standard
20
jlt sbgtools f2b
21
eifel mail forms protus
22
gränna hem pc scs
23
jobb email alviva
24
jupiter
servicebilar
gdp phoenix
25
job mail password
This ends our result section and we shall now
discuss these findings and their implications.
5 DISCUSSION
When comparing our tables with results from studies
of the public web, we immediately see that the
search terms used in public search engines differ
significantly from the terms and queries we found at
Jupiter. This is not at all surprising and echoes the
findings of Chau et al. (2005) who noted that terms
used in site searching were very different from those
used in general-purpose search engines. For
example, neither we nor Chau et al. found many sex
related terms, whereas such terms often dominate
the ranking list from public search engines. The
focus of this work is not on the query terms per se
since these will vary from setting to setting, but on
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the method of analysing search behaviour and
information needs and on the patterns that can be
observed when examining search queries over time.
Studying table 2, one can come to the conclusion
that jupiter is a rather common query. This is only
partly true; jupiter is indeed a frequently used term
but not a frequently used query. In fact, “jupiter” as
a stand-alone term occurs only in 34 of the 2,782
queries that includes the term jupiter. In 98.78% of
the jupiter-related queries, the term jupiter is
combined with other terms, which can be seen also
from tables 3 and 4. The term jupiter does thus not
represent the information need; this can instead be
found in the other part of the pair (such as in “jupiter
lift”) or triplet (such as in “jupiter golf
competition”). So although table 2 is correct in a
statistical sense, such listing of individual terms may
skew the understanding of the search behaviour.
Term frequency lists are presented in much of the
published research in this area (cf. Jansen & Spink,
2005; Spink et al., 2001; Jansen et al., 2000), but we
argue it may be better to instead list the most
frequently submitted queries or to include the most
frequently used pairs and triples, as do Chau et al.
(2005). Only half of the most frequently used terms
overlapped with the most frequently submitted
queries. If we see differences between term
frequencies and query frequencies already on an
intranet where the average query length is 1.44 terms
and 69% of the queries are single term queries
(Stenmark, 2005b; 2006), this difference would
probably be even more evident on the public web
where the average query length is closer to 2.5
terms. This further underlines the need to look
beyond mere query term analysis when trying to
understand the information needs of search engine
users.
As in Chau et al.’s (2005) study, our study shows
that the frequencies for the highest ranked term pair
is considerably lower than the frequency of the
highest ranked term, and that the frequency for most
sought for triplet is lower still. We also note the drop
is much more pronounced in our data than in Chau
et al.’s study. In addition, the slope of the Zipf plots
in figure 1 is not as steep as theory would have it.
These observations suggest that a larger portion of
single term queries are used at Jupiter. Referring to
Fagin et al. (2003), we suggest that this is because
intranets contain more jargon and more acronyms
than do the public web. Another possible
explanation suggested by Stenmark (2005b; 2006) is
the presence of Swedish terms. The Swedish
language makes use of compound words, resulting
in single terms where e.g. English would have used
two terms.
We were expecting there would be more unique
search terms on a general-purpose search engine
than on a site-specific one, but Jansen et al.’s (2000)
slope of -0.975 for Excite terms is very close to
Chau and colleagues’ slope of -0.9533 for the Utah
search engine. A single web site can be expected to
be more narrow in coverage and thus have a more
limited vocabulary, and we were expected this to
show in the distribution of search words. We had
originally been expecting the Zipf plot of an intranet
search engine to fall somewhere in between the Utah
and the Excite plots but now our slopes of around -
0.85 are less steep than both the other. We posit that
the Swedish way of constructing compound words
make the number of terms grow quicker than the
frequency, hence producing these results. Additional
(linguistic) analysis is required to fully understand
this issue. It would be interesting to compare our
findings to those from other intranet using other
languages, say Finnish or English, to try to establish
what is intranet dependent and what dependents on
the language.
As was evident from table 1, the top terms
portions of the total are pretty consistent over the
years, i.e. a relatively small subset of the terms is
used again and again. The portion of hapaxes (i.e.,
not repeated words) is not equally stable, although
the variances are rather small. Close to 60% of the
query terms are used only once, but since the
repeated words are sometimes used very frequently,
the hapaxes only make up some 15-19% of the total
corpus. Still, 15-19% is a significant portion and it
indicates that the information need is focused on
quite a narrow field. When studying the top-100
terms, we noted that although more than half of the
terms were present only in one year, some 17% of
the terms reappeared every year. This distribution
holds also for the top-10 terms. The corresponding
numbers for the top-100 queries are similar; some
12% of the queries are found across all years.
Apparently, there are things that the Jupiter
employees continue to search for year after year,
indicating what we mean is a long-term information
need. Information about such needs would be useful
to information providers and site designers within
the organisation. Chau et al. (2005) argue that such
frequently sought-for information should be made
accessible via prominently placed links.
However, we see that the portions of terms and
queries not repeated are bigger and we posit that the
large portion of unique terms and unique queries
indicate that there is a shift in information seeking
behaviour from year to year. These queries may
indicate the short-term information needs. These
needs may be further be seasonal, as suggested by
Chau et al. (2005). It seems plausible the
information about the Jupiter golf competition will
be more attractive closer to the actual event. The
shift in information needs that this data suggest may
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127

also stem from a re-organisation of the available
information or a re-make of the intranet. We suggest
qualitative studies be carried out to explore this issue
in more depth.
Our study also shows that a large international
organisation may have a multi-lingual intranet,
despite an official corporate language (English in
this case). This stresses the importance of multi-
language information retrieval research. Search
engine vendors aiming for the intranet market should
closely follow this development and preferably form
joint ventures with multi-lingual retrieval researcher
to help push the frontier further. In addition, the
large number of indeterminable terms also point to
the need for research on how to correctly deal with
synonyms and homonyms in information seeking.
There are several organisational implications to
be drawn from this study. Some information needs
appear to be persistent and time-independent and
organisations should adjust their information
provision accordingly. This means that adding
information, updating it, highlighting it, adding
metadata to it and linking to it from many places are
important activities for the organisation once these
needs are identified. Search engine log file analysis
may thus be a useful tool when assessing the effects
of information architecture remakes and new web
site designs. Other information needs are more
short-term; they emerge and disappear in short
cycles, but may still be very important to the
business. To be able to respond to such shifting
information needs, organisations must closely
monitor the queries and be quick to provide the
required information. As we have illustrated, it is not
enough to study the most frequently used terms, but
the whole query.
There are also obviously limitations to this
study. Although we have used data from three
different years and thus been able to follow the
development of the queries, our study is limited to
one intranet. This is understandable, since a lot of
work is required to analyse this amount of data, but
our findings still have to be replicated and tested
elsewhere before any far-reaching conclusions can
be drawn. In our qualitative analysis of the data we
have restricted us to the most frequently used terms
from each year. It is possible that this has skewed
the outcome of the analysis and that our findings do
not represent the corpus as a whole. This also has to
be taken into consideration.
6 CONCLUSIONS
We have studied three log files from a corporate
intranet search engine; one file from 2000, one from
2002, and one from 2004. Having extracted the
actual queries and the query terms we have been
able to analyse what the organisational member have
sought for and how their information needs have
shifted over time.
It is common practice to use query term
frequency lists to illustrate information needs. In this
paper we have shown that this may produce
misleading conclusions since single words in
isolation carry very little information. More useful is
to present the most frequently used queries or the
most frequently used term pairs or term triplet, since
this approach allows for more context.
The Zipf plots from our intranet study show
slopes that are less steep than those produced by
both public search engines and web site search
engines. This means that new terms are used more
often than expected and further research is needed to
show if this holds for intranet search in general.
The majority of the queries and query terms are
replaced from year to year. This suggests that short-
term information needs fluctuate and are time-
dependent. Organisations must thus continuously
keep track of the current and emergent needs and be
ready to provide the corresponding information.
However, we also conclude that certain information
needs are rather persistent and time-independent and
organisations should focus on providing content in
these areas. The Zipf-like distribution means that
only a fraction of the queries need to be catered for
in order to cover much of the information needs.
ACKNOWLEDGEMENTS
The author is grateful to the Jupiter corporation for
providing access to their log files, to Artur
Foxander, Richard Wallmark and Taline Jadaan for
help during the data processing, and to the reviewers
for constructive critique. This work was sponsored
by the Swedish Council for Working Life and Social
Research (FAS) via grant #004-1268.
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