LIBRES: Library and Information Science Research
Electronic Journal ISSN 1058-6768
2001 Volume 11 Issue 2; September 31
Bi-annual LIBRES 11N2
DESCRIPTION
http://publish.uwo.ca/~craven/index.htm
Timothy
C. Craven
Faculty
of Information and Media Studies
The
(519)-661-2111
ext. 88497. Fax: (519)-661-3506.
Abstract
Random samples of 1,872 web pages
registered with Yahoo! and 1,638 pages reachable from Yahoo!-registered pages
were analyzed for use of meta tags and specifically those containing
descriptions. Seven hundred
twenty-seven (38.8 percent) of the Yahoo!-registered pages and 442 (27.0
percent) of the other pages included descriptions in meta tags. Some of the
descriptions greatly exceeded typical length guidelines of 150 or two hundred
characters. A relatively small number (ten percent of the registered and seven
percent of the other pages) duplicated exactly phrasing found in the visible
text; most repeated some words and phrases. Contrary to documented advice to
web-page writers, pages with less visible text were less likely to have
descriptions. Keywords were more likely to appear nearer the beginning of a
description than nearer the end. Noun phrases were more common than complete
sentences, especially in non-registered pages.
Introduction
This article reports on work designed to
extend a preliminary investigation (Craven, 2000a) of how people and
organizations summarize their own web pages and, specifically, how and to what
extent they make use of meta tags, especially those with the NAME attribute
equal to DESCRIPTION.
The background to this investigation was
research conducted over a number of years directed toward developing a
prototype computerized abstractor's assistant (Craven, 1988, 1991, 1993, 1996,
1998). As a kind of writer's assistant, such a software package includes a
simple word processor and other general writer's tools (Kozma, 1991) with their
functioning adapted to fit the needs of abstractors and writers of other kinds
of short summaries. In addition, the package integrates such tools as an
automatic extractor, related specifically to the task of summarizing. In
addition, Paice (1994) has provided a list of desirable features for such a
package.
A hybrid system, in which some tasks are
performed by human abstractors and others by software, appears to be an
appropriate short-term goal since purely automatic abstracting methods (Paice,
1990, 1994; Endres-Niggemeyer, 1998, pp. 297-366; Pinto & Galvez, 1999) do
not show immediate promise of totally superseding human effort.
At least two possible benefits are
expected from the study of web-page authors' actual practice in summarizing
their documents in meta tags. The first of these is in the design of software
to assist authors in tag generation.
This expectation is based in part on an assumption that author-created
descriptions will reflect features that authors and other users consider
desirable. The second anticipated benefit is in browser design: to know whether
introducing a feature to display the description, as, for example, a title is
commonly displayed in the caption bar, would benefit visitors to a substantial
number of web sites (compare Beagle, 1999).
Other aspects of the content of web pages
have been studied by various researchers. King (1998), for example, studied
page layout of library home pages; Haas and Grams (2000) concentrated on
characteristics of the anchors found in randomly selected pages; Almind and
Ingwersen (1997) applied informetric measures; and Harter and Ford (2000)
studied links to e-journals and their articles. Little investigation has been
done of the meta tag with NAME='DESCRIPTION' (hereafter referred to as the
DESCRIPTION tag). Turner and Brackbill (1998) do report the results of a small
experiment that showed that the addition of a DESCRIPTION tag did not improve
retrievability of web pages on Infoseek and Altavista.
Advice provided in both printed and
web-based sources on the function, content, structure, and style of the
DESCRIPTION tag has been reviewed elsewhere (Craven, submitted). What follows
is a brief summary of the main recommendations garnered from that review.
1. The DESCRIPTION tag can be used for an
abstract.
2. Tag contents should not be deceptive.
3. A description is particularly useful for
documents with little text.
4. The
description should be no more than two hundred characters (though some
recommended maximum range from one hundred to 256). There is a more absolute
technical upper bound of around one thousand characters.
5. The description should be concise.
6. The description should reflect the single
page, a whole site, or both (advice varies).
7. A number of keywords should be included in
the description.
8. The most important words should be near the
beginning of the description.
9. The description should not be the same as the
title.
Sample descriptions in the sources showed
various patterns. Some contained what appear to be formulaic elements such as
"Home page for"; others did not.
It has been noted that there is also a
DESCRIPTION element in the Dublin Core (2000), defined as "an account of
the content of the resource," with the further comment that it "may
include but is not limited to: an abstract, table of contents, reference to a
graphical representation of content or a free-text account of the
content." As a meta tag, this element appears in standard form with the
name DC.DESCRIPTION.
Sample
Methodology
In order to estimate the total variety of
use of the DESCRIPTION tag, it is desirable to obtain a broad, representative
sample of publicly available web pages, especially of those pages employing
meta tags, in particular the DESCRIPTION tag. A survey of forty-two search
engines (in December 1999) (Craven, 2000) revealed no feature on any that
permitted searching for specific meta tags. In terms of sampling web pages in
general, Askjeeves and Webcrawler permitted peeking at sample queries,
OpenDirectory selected random categories if an empty query was entered, and
All-In-One's "What's New Too" option showed the day's announcements
of new pages.
Since a sufficient proportion of pages
indexed by Yahoo! used meta tags, including the DESCRIPTION tag (twenty-six
percent), it was feasible to proceed by sampling from these pages. At that
time, an application program was created in
In the preliminary study, only pages
returned directly by Yahoo!'s random page service were used (level-one pages).
Since such pages were presumably registered with Yahoo!, it may well be that
they were also registered with other web search services. Although Yahoo!
ignores meta tags, the pages' creators may have been particularly sensitized to
the value of meta tags for some of these other search services. Thus, in order
to investigate possible differences in non-registered pages, the present study
added two other types of page: a page reachable by following a random link from
a page returned by the random-page service (level-two page) and a page
reachable by following a random link from a level-two page (level-three page).
Requests for random pages were submitted to Yahoo! by a research assistant over
a period of twenty-five days. The aim was to retrieve at least eight hundred
pages at each level. Because the initial set of pages at level one was gathered
in a mode that included page rendering and downloading of inline image files
while the pages at levels two and three were retrieved with these options off,
the assistant also collected an additional set of pages at level one with the
mode matching that of levels two and three.
This was performed about one month after the original level-one set.
Within each set, a test for duplication
of uniform resource locators (URLs) was carried out for those pages containing
DESCRIPTION tags. The number of links
on each page was also recorded. Included in this count for purposes of this study
were not only links defined by hypertext reference (HREF) values in anchor (A)
and area tags but also links defined by source (SRC) values in frame tags.
Results
A natural multiplier effect meant that
the proportion of successful downloads decreased as level increased. For example, to obtain the first two hundred
level-one pages required only 274 requests, a success rate of seventy-three
percent, but to get the first two hundred level-two pages required 448
requests, for a success rate of 44.6 percent. It had been established in the
preliminary study that the most common reason for failure (nearly four out of
five) was timing out, usually with a "not found" or "404"
message displayed in the hypertext markup language (HTML) viewer. The number of
successful downloads was 833 for the first set at level one, 821 at level two,
817 at level three, and 1039 for the second set at level one.
As shown in Figure 1, the proportion of
pages containing meta tags held very close to sixty-seven percent at all three
levels; the proportion in the preliminary study had been somewhat lower at
fifty-seven percent. The proportion containing the DESCRIPTION tag specifically
was noticeably higher at level one (38.4 percent and 39.2 percent) than at
level two (26.1 percent) and level three (27.9 percent).
Only one case of duplication of a URL was
found among the pages with DESCRIPTION tags, at level 3.
Pages with descriptions typically
contained a number of links, with means somewhat above the fifteen calculated
in the preliminary study (19.7 at level one, 23.9 at level two, 22.7 at level
three). The maximum number of links on a page was 326 (at level three). As in
the preliminary study, few pages had no links (two and three at level one, one
at level two, and one at level three).
Repeating the findings of the preliminary
study, very few pages used Dublin Core elements (two and two at level one, one
at level two, and one at level three). Three of these included a Dublin Core
description, in one case without a DESCRIPTION tag, in one case with a
DESCRIPTION tag with the same value, and in one case with a slight difference
in the wording of the two tag values.
Discussion
The proportion of pages using meta tags
was even more noticeably above that of the 24.4 percent reported by Qin &
Wesley (1998) for pages in polymer chemistry than had been the case for the
preliminary study. The proportion of pages using the DESCRIPTION tag at level
one was noticeably greater than the proportion at levels two and three, which
were close to the twenty-six percent found in the preliminary study and much
above the figure of about twenty-one percent using meta tags with both the
names KEYWORD and DESCRIPTION cited by Clark (2000). The higher rate of page
tagging at level one would seem to support the hypothesis that developers are more
likely to pay attention to tagging for pages that they will be submitting to
search services.
Errors excepted, it appears that the
pages returned by requests to the Yahoo! random-page generator are generally
home pages. A rough confirmation of this conclusion can be obtained from
statistics on the forms of the URLs. Only 178 and 243, or 21.4 percent and 23.4
percent, of the URLs for the level one pages contain the string
".htm" (which would include both the ".htm" and the ".html"
extensions). Although some of the others will represent other file formats,
most of them are simply references to the default pages delivered by servers
for their root or other directories. By contrast, 611, or seventy-four percent,
of the level-two pages and 621, or 76.1 percent, of the level-three pages
contain ".htm" in their URLs.
The extremely low level of duplication of
URLs confirms that the Yahoo! random-page service gives access to a large
sample of web pages and suggests that page duplication as such would not be a significant
concern in future studies involving this method of selection. On the other
hand, there was some evidence of a minor concentration of results on certain
sites, most noticeably that of the Toronto
National Post, for which the service, at various levels, returned a total
of thirty-three pages with the same description.
Comparison
of Descriptions with Visible Text
Purpose
Two main questions were posed regarding
the relationship of the description to what the user would actually see in the browser
window. First, are pages with little visible text more likely to be given
descriptions as is recommended by some of the sources? Second, to what extent
do the descriptions merely repeat words or phrases that are visible on the
pages?
Methodology
Visible
text was defined as all text that was not
part of a tag. This would typically include the page's caption title and most
text normally displayed as text in the viewer. Visible textual material that
would be excluded would include button captions in forms and any text loaded as
part of a frame. Text appearing in graphic form would also be excluded as would
any alternate text (ALT) values given in the image (IMG) tag.
A description
was defined as the value given to a DESCRIPTION tag in a downloaded file.
Degree of match of each description to
the corresponding visible text was calculated for words and phrases. The
measure used for words was the density of non case-sensitive matches of
visible-text words within the description. The measure used for phrasing was
density of non case-sensitive matches of visible-text two-word sequences within
the description. A word was defined as any sequence of alphabetic characters
delimited by other types of characters. In addition, the longest visible-text
word sequence found in each description was logged; in the case of a tie, the
tied sequences were all logged, separated by a delimiter, in a single record.
Results
Lengths of the visible text varied
between 0 and 178,637 bytes. The median length increased somewhat with level
(565.5 and 647 for level one, 764.5 for level two, and 896 for level three).
Shorter visible texts were significantly less likely to be associated with
descriptions, even leaving aside those pages with no visible text (with p <
0.0001 in t-tests applied to the logarithm of number of characters in visible
text).
As shown in Figure 2, the descriptions
were generally relatively short. The mean length was just over twenty words at
all levels (21.9 and 24.2 at level one and 21.3 and 20.9 at the other two
levels). But they could be fairly long, with the longest being 173 words (the
preliminary study had found one at 294 words). The shortest that contained any
words consisted of the single words "strong" and "test." Using a different measure, 181 and 238, or
56.6 percent and 58.5 percent, were no more than 150 characters in length at
level one; 128, or 59.8 percent, at level two; 142, or 62.3 percent, at level
three; and 243 and 310, or 75.9 percent and 76.2 percent, were no more than two
hundred characters at level one; 165, or 77.1 percent, at level two; and 178,
or 78.1 percent, at level three. The longest was 839 characters.
The density of visible-text words in the
descriptions ranged from zero percent to one hundred percent, with means of 87.1
percent and 91.3 percent at level one and 84.9 percent and 82.2 percent at the
other two levels. As is clear from Figure 3, the distribution was heavily
skewed toward the high end. This was especially true at level one, where 186
and 277, or 58.1 percent and 68.2 percent, of the descriptions had a
visible-text word density greater than ninety percent, figures somewhat higher
than the fifty-two percent observed in the preliminary study. The skew was also
found, to a declining degree, at the other levels, where 105, or 49.1 percent,
and ninety-three, or 40.8 percent, showed a density of greater than ninety
percent. Visible-text word density was in fact one hundred percent for 117 and
168 descriptions, or 36.6 percent and 41.4 percent, at level one, sixty-eight
descriptions, or 31.8 percent, at level two, and sixty-two descriptions, or
27.2 percent, at level three.
In contrast, the distribution of density
of visible text phrasing, as shown in Figure 4, appears to be bimodal, as noted
also in the preliminary study, with one local maximum somewhere in the twenty
to fifty percent range and another in the ninety to one hundred percent range.
In a number of cases (thirty-six and forty at level one, thirteen at level two,
and eighteen at level three), the density was one hundred percent, meaning that
the entire description was word-for-word a sequence also found in the visible
text. Many such descriptions were short, but the longest (at level three) was
sixty-two words, exceeding the forty-six-word record set in the preliminary
study.
This entire description of sixty-two
words (http://octopus-design.co.uk:80/octopus/home-nos.htm) was also the
longest word sequence in a description that exactly matched one in the visible
text:
Octopus
Design are a team of graphic design professionals utilising the latest computer
technology to assist a wide range of skills effectively and creatively. If you
are looking for a design company who are committed to supplying top quality
graphic design solutions on time and on budget, why not view our portfolio
here, e-mail us for more information or telephone.
Discussion
As in the preliminary study, the
suggestion of one source that descriptions are especially important to pages
with little visible text was not reflected in practice: pages with less visible
text were actually less likely to contain the DESCRIPTION tag at all levels.
This observation does not, of course, invalidate the advice.
The great majority of the descriptions conformed
to the common maximum-length guideline of two hundred characters. A smaller
majority conformed to the more restrictive guideline of 150 characters given by
HotBot and others. The fact that more than twenty percent of descriptions at
all levels, as in the preliminary study, exceeded the two-hundred-character
limit, in one case reaching more than four times that number of characters, may
suggest that there is a need on the part of some authors for a way of including
much longer descriptive information. The one description in the preliminary
study that was almost nine times the recommended maximum length seems, however,
to have been particularly anomalous, exceeding even the more technical limit of
one thousand characters.
The bimodal appearance of the phrasing
density distribution clearly suggests at least two approaches to authoring
descriptions: on the one hand, production of an expression that is original but
that substantially echoes wording found in the visible text and, on the other
hand, exact copying of an entire expression from somewhere in the visible text.
It is expected that future research will examine which parts of the visible
text tend to be duplicated in the latter situation. For example, is it the
first two hundred words as suggested by some of the existing guidelines?
Since most descriptions are not
word-for-word repetitions of information provided in the visible text, a
browser feature to display the description might be of value to some users.
Such a feature would need to take into account that some descriptions are quite
long. A single line, like the caption bar used for titles, would not be
sufficient (indeed, even titles of web pages are sometimes too long to fit into
the space available in the caption bar). The increasing complexity of HTML is
making it more and more difficult for a user to access non-display text by the
alternative expedient of viewing the page source.
Given the number of links on the typical
page, it seems reasonable to assume that, in many cases, the descriptions are
intended to apply to a site or collection of pages rather than to a single
page. A related study, not yet reported on, used the variation of appending the
visible text of linked pages to the visible text of the initial random page. As
hypothesized, both word-match and phrase-match density within the descriptions
increased substantially with the addition of the linked-page texts, suggesting
that the descriptions are indeed intended to apply to multiple pages. Another
test, to be carried out in the future, will compare the results of following
only local links to see whether authors are more likely to use descriptions for
sites rather than for multi-site groupings of pages.
Conciseness
and Structure
Purpose
Questions to be addressed under the
heading of conciseness and structure included the following. Are descriptions
generally concise, as recommended, and how does their conciseness compare with
that of scholarly abstracts? Do descriptions use complete sentences, as
recommended for abstracts, or do they tend to consist of title-like noun
phrases or other syntactic structures? Are home-page descriptions more likely
to use complete sentences than descriptions for other pages? Is formulaic
phrasing, as suggested by some of the samples provided by the sources, at all
common?
Methodology
Simpson's l (Simpson, 1949), a measure of
concentration or repetition of vocabulary equal to the probability that the
words occurring at two different random locations in a text are the same, was
computed for each description as a possible negative indicator of conciseness.
All descriptions were analyzed for
general syntactic structure. For this purpose, each description was considered
to be divided into segments by sentence-level punctuation marks: periods, exclamation
marks, and question marks. Each segment was then categorized as a noun phrase
or sequence of noun phrases (n), a verb phrase or sequence of verb phrases (v),
an adjectival or adverbial phrase or sequence (m), a sentence in the indicative
mood (s), a sentence in the imperative mood (c), or other (o). For example, the
description "Marshall Media produces high-quality CD-ROMS for children and
adults. Order online from our shop." would be coded sc.
To estimate inter-rater reliability, the
research assistant was first asked to re-code sixty-five descriptions
previously coded in the preliminary study. Consistency on this test was 90.8
percent on all codings and rose to 95.4 percent when all codings except n, nn,
s, and ss were collapsed into a single "other" category. Reliability
was thus deemed more than sufficient for the assistant to proceed with coding
the main description sets independently.
Results
Values for Simpson's l were similar across
the levels, with means of 0.0127 for both level one sets and 0.0108 and 0.0136
for the other two levels, and ranged from 0.0000 to 0.2273. The most common
value was zero, generally in shorter descriptions, though the longest was
thirty words: ""Desertcom - Just what you've come to expect!!! A
15-year history of tradition with
The most common words in the descriptions
(at least one occurrence for every thirteen descriptions), apart from obvious
stopwords, were as shown in Table 1.
.
|
Table 1: Common words in descriptions |
|||||||
|
Level 1a |
Level 1b |
Level 2 |
Level 3 |
||||
|
DESIGN |
27 |
BUSINESS |
37 |
BUSINESS |
23 |
DESIGN |
20 |
Common syntactic patterns are shown in Table 2.
|
Table 2: Syntactic patterns |
||||||||
|
|
Level 1a |
Level 1b |
Level 2 |
Level 3 |
||||
|
n |
113 |
36% |
155 |
39% |
91 |
44% |
107 |
52% |
|
nn |
13 |
4% |
27 |
7% |
14 |
7% |
5 |
2% |
|
s |
72 |
23% |
73 |
18% |
41 |
20% |
35 |
17% |
|
ss |
30 |
10% |
36 |
9% |
14 |
7% |
9 |
4% |
|
other |
87 |
28% |
109 |
27% |
48 |
23% |
50 |
24% |
In
the "other" category, eighty-three descriptions contained imperative
(c) segments, almost always at the end, in eighteen instances after a single
indicative-mood (s) sentence. The largest number of segments in a description
was eleven, where the segments all consisted of brief noun phrases separated by
periods.
Discussion
The average values for Simpson's l for
descriptions were similar to those in the preliminary study and only slightly
lower than those observed in a previous study of abstracts produced with
computer assistance (Craven, 2000b).
ONLINE, SERVICE, INFORMATION, INTERNET,
and SERVICES had all been noted as among the most common words in the
preliminary study. All the occurrences of ESTATE and all but one occurrence of
REAL at level two were in the phrase REAL ESTATE, which was fairly concentrated
in two descriptions but appeared in others as well. The word pair REAL+ESTATE
was noted as the eighth most common in Wolfram's (1999) study of term
co-occurrence in Excite queries. NUDE, PICS, and XXX were among words that were
common in the queries analyzed by Wolfram but occurred only a couple of times
each in the descriptions.
Noun phrases or sequences of noun phrases
were much more common than one might expect in an abstract, especially as one
progressed from level one to levels two and three. The increasing preference
for noun phrases with level would be consistent with some tendency to apply
abstract-like descriptions more to home pages or pages to be registered with
search services and to apply subject-heading or title-like descriptions more to
other, especially subordinate, pages on a web site.
Imperative-mood sentences would not be
expected in abstracts, and they were relatively rare in the web-page
descriptions in spite of the presumably promotional nature of many of the sites
and the use of imperatives in some of the descriptions provided as models.
Comparison
with Keywords
Purpose
The main questions to be addressed in
comparing keywords were the extent to which keywords were in fact found in
descriptions and whether the advice to place keywords near the beginning was
followed. The amount of repetition within keyword lists was also of interest.
Methodology
Wording and phrasing of descriptions were
compared to the contents of any meta tag with a name attribute of KEYWORDS in a
fashion similar to that applied for the visible text. In addition, the mean
position of keyword matches within descriptions was calculated. Simpson's l was
used to measure repetition within keyword lists.
Results
The density of keywords in the
descriptions ranged from zero percent to one hundred percent but averaged close
to the thirty-eight percent value observed in the preliminary study (36.9
percent and 36.7 percent at level one, 38.9 percent at level two, 39.9 percent
at level three).
As in the preliminary study, density in
the descriptions of two-word sequences from the keywords showed a local maximum
in the zero-ten percent range at all levels. No keyword word pairs were found
in just under one-third of the descriptions at all levels (ninety-three and 110
at level one, sixty-six at level two, and sixty-five at level three). Again, a
small number consisted entirely of keyword word pairs (five at level one, four
at level two, and four at level three); the longest of these was 147 words
(<http://www.transdev.com/
eudora="autourl">http://www.transdev.com:80).
The mean position of keyword matches was
significantly more likely to be nearer the beginning of the description than the
end at all levels (0.0000 and p=0.0001 at level one, p=0.0015 at level two,
p=0.0001 at level three using a chi-squared test), with the average position
being around forty-five on a 0-100 scale. As in the preliminary study, length
of the keywords had a low positive correlation with length of description
(0.2262 and 0.2146 at level one, 0.1962 at level two, 0.2934 at level three).
For keyword lists, Simpson's l was
generally higher than for the descriptions, with means of 0.0301 and 0.0269 at
level one and 0.0222 and 0.0260 at the other two levels, and ranged from 0.0000
to 0.5000. The highest value was observed in the clearly repetitive
"sturgis, sturgis rally, STURGIS, STURGIS RALLY, Sturgis, Sturgis
Rally" (<http://www.sturgiscamping.com/ eudora="autourl">http://www.sturgiscamping.com:80).
Discussion
The results on average position of
keyword matches represented an addition to the preliminary study where
statistical significance had not been attained. They do supply some support for
the hypothesis that description developers/writers are following the advice to
put keywords near the beginnings of their page descriptions, but the tendency
does not appear to be very strong.
The slightly higher but still modest
values of Simpson's l for the keyword lists are not consistent with a view of
developers as engaged in widespread "word stuffing" to increase
retrievability of their pages. There are obviously some exceptions.
Conclusion
From this study, the following main
findings have emerged:
1. Pages with
little visible text are actually less likely to be given descriptions, contrary
to what is recommended by some of the sources.
2. Descriptions
vary greatly in their repetition of words and phrases that are visible on the
pages: some repeat word for word; others repeat selectively.
3. Descriptions generally appear about as
concise as scholarly abstracts.
4. Unlike
abstracts, many descriptions tend to use noun phrases rather than complete
sentences. Use of complete sentences appears to be slightly more characteristic
of descriptions on home pages.
5. While
some words are found fairly frequently in descriptions, there is little
indication of widespread adoption of formulas.
6. Keywords
are found in descriptions to various extents. They have a slight tendency to
appear nearer the beginnings than the ends of descriptions, reflecting in a
very weak fashion the advice to place them up front.
7. On average, keyword lists are not highly
repetitive.
In future research, it would be useful to
rate a sample of descriptions for quality, using either objective criteria or
subjective human judgments or both. Even scholarly abstracts have sometimes
been found to be of poor quality. Pitkin, Branagan, & Burmeister (1999),
for example, demonstrated inconsistencies and other defects in published author
abstracts. Inter-rater reliability might, however, be expected to be low. In a
study in which subjects rated different abstracts of the same document on
various criteria, agreement was sometimes very poor (Craven, 2000b).
A very simple kind of assistance for
web-page developers is already provided in WordPerfect, namely, copying any
abstract into the DESCRIPTION tag when exporting to HTML. Conceivably, the
abstract or description might also be automatically copied to the corresponding
Dublin Core tag. Dublin Core elements were, however, rarely encountered in this
study and the DC.DESCRIPTION meta tag appears to be redundant, especially if it
merely duplicates the DESCRIPTION tag.
If more advanced tools are to be produced
to assist in the adding of appropriate meta tags to HTML documents, it is
likely that different tools will suit different types of users. That
individuals use quite different approaches in writing abstracts has been noted
in studies involving think-aloud protocols (Endres-Niggemeyer, Waumans, &
Yamashita, 1991); similar observations are to be expected regarding the writing
of other kinds of summary. For composing web-page descriptions specifically,
results of the present study suggest that some authors might want a tool for
copying text from elsewhere on the page while others might find automatically
generated lists of key words or phrases to be helpful.
Acknowledgments
Research reported in this article was
supported in part by individual operating grant A9228 of the Natural Sciences
and Engineering Research Council of Canada.
The extensive assistance of research
assistant Michael Dub in data gathering and categorization is also
acknowledged.
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