Adjusting to Specialties of Search Engines Using MetaWeaver
Mikihiko Mori and Seiji Yamada
CISS, IGSSE, Tokyo Institute of Technology
4259 Nagatsuta, Midori, Yokohama 226-8502, Japan
mori@ymd.dis.titech.ac.jp
Abstract:
In this paper, we propose MetaWeaver which can selectively utilize effective ones from registered search engines depending on queries. Traditional meta-search engines use all the registeredsearch engines without considering which search engines are appropriate, and often return manyirrelevant Web pages in the hit list. In contrast with that, MetaWeaver is able to evaluate the specialties of each search engine by analyzing the hit list for sample queries, and to utilize them forselecting adequate search engines for current queries. Also we found out our approach is promisingby making preliminary experiments.

1Introduction

There are currently a lot of search engines to retrieve relevant Web pages to a query from the World Wide Web(WWW). In view of the characteristics of the stored Web pages, the search engines are categorized into twogroups. One group is general all-round search engines like AltaVista [1] . The other group is special search engines
like DogInfo[2] , which is a dog-specific search engine. Because a general search engine have a huge database, we
use it for searching any query. However there is a significant issue that the coverage of a general search engine issignificantly insufficient. The Web size and the size of each search engine’s database were surveyed in (Bharat &Broder 1998). The largest search engines covered 50% of all of the Web pages and maximum overlap of searchengines is 30%. Thus a user can not search well using a single general search engine.
A meta-search engine solves the issue by ask other search engines about the queries. It does not collect pages
in the Web by itself. Instead it registers other search engines in advance, and requests them to retrieve for thequeries and gather their results. Then the meta-search engine provides a hit list of Web pages by integrating thehit lists from other search engines and removing overlapping pages. However a meta-search engine also has asignificant problem: it can not selectively utilize registered search engines depending on their specialties. Henceit always requests all the registered search engines and the integrated hit list include many irrelevant Web pages.
Though some meta-search engine ask a user to select adequate registered search engines, he/she hardly recognize
specialties of each search engine on the queries and select effective ones from them.
We propose MetaWeaver which can grasps specialties of each search engine and request search engines whose
specialty is content of the queries. When it estimates search engines, it uses thesaurus for improvement of estimate.
Therefore, it is expected that Web pages from it satisfies user’s queries more precisely than traditional meta-searchengines.
MetaCrawler (Selberg & Etzioni 1997) requests all handled search engines in parallel and removes duplication.
Inquirus (Lawrence & Giles 1998) also submits all search engines. However, it downloads the Web pages in hit
lists from the search engines and then, it calculates relevance to the query using downloaded pages.
On the other hand, ProFusion (Fan & Gauch 1999) selects appropriate search engines to request them tosearch. It manually builds categories from the words of the newsgroups names and it can only select when thewords include words of user’s query.
SavvySearch (Howe & Dreilinger 1997) can also select proper search engines. It uses words of users’ queries
and their effectiveness values. Visited links by users evaluate the value. SavvySearch, however, does not use anythesaurus. Therefore, it will not evaluate search engines on initial steps of searches.

[1] http://www.altavista.com/[2] http://www.doginfo.com/

2MetaWeaver

Meta-search engines need to choose proper search engines for queries a user requested. MetaWeaver can detect
effective search engines by the word used as in queries. The architecture is shown in Figure 1.

Facilitator
Queries

Thesaurus

Hit ListUser

Word & Hits
Database

Browser
Selection

Search Engines
Figure 1: The architecture of MetaWeaver

2.1 Search Overview
A user writes queries to the meta-search engine to submit them on a his/her browser. Users can make queries asAND, OR search or these combinations.
The facilitator selects some search engines from registered search engines as appropriate search engines of theuser’s query when a user make a submission. We define a suitability to choose appropriate search engines and thedetail of suitability is described in section 3.
The facilitator send user’s query to selected engines in parallel. It waits while all engines return lists of top 10hits. When it gets the hit lists, it integrates into a hit list to display the user’s browser. The way of integration formaking the meta-search hit list is described in section 4.
The suitability is updated after the user gets the hit list. The suitability of each word in the query is based on
the number of hits of the word. Therefore, the facilitator gets the number of hits of each word from each of all
registered search engines and writes the numbers into the word and hits database with search engine names. Thus,
MetaWeaver behaves adaptively toward the changes of search engines’ databases.

2.2 System Requirements
MetaWeaver utilizes AltaVista[3] , Yahoo[4] and Infoseek[5] as general search engines and also utilizes DogInfo[6](a dog specific search engine), BioCrawler[7] (a biological search engine) and LawCrawler[8] (a law search engine)as specialty search engines.
For thesaurus, MetaWeaver utilizes the EDR Electronic Dictionary [9] that contains the relation between four
hundred thousand concepts.

3

Calculation of The Suitability

MetaWeaver needs to measure the suitabilities for choosing appropriate search engines. The appropriate searchengines is regarded as search engines which returned large number of hits according to queries before. Larger hits
tend to be less precision, which is the relevant pages per hit pages, but more relevant pages actually include.
In this section, we present a method to measure the suitability of a single-word and a combined-word query.
3.1 A Single-word query
When a query consists of a single word, the suitability p s,w of a search engine s for word w is the number of hits
divided by the size of search engine s:
us,w
ps,w =(1)Us
where us,w is the number of hits from the word and hits database and U s is the search engine’s size.
However, it is not usual that the search engine opens its size. Therefore, MetaWeaver uses the history of hits
from the word and hits database for the last f s words of each search engine. fs is currently 100. We express Us
instead of exact search engine size as follows:
Us = αufs
us,wn−i(2)i=1where uwn is the number of hits of the nth word from the last and α u is the correction factor for approximating
summation of us,wn to Us .
Here, the thesaurus improves ps,w . If MetaWeaver does not use any thesaurus on initial steps of searches, itdoes not initially decide right estimation of search engines for choosing appropriate ones because it estimates thesuitability at zero not to have the number of hits about the words in a query in the word and hits database.
By using thesaurus, MetaWeaver to be able to compute p s,w not only when w do not have any records in theword and hits database but also when w have records. The suitability after improvement by thesaurus is described:
δw,m ps,w
imp
ps,w = ps,w + m∈Wt
(3)
|Wt |
where pimps,w is the improved suitability, p s,w is the suitability of each word in a synonym set W t and δw,m is theweight of relation between w and a synonym m. δ w,m between each word and each of its synonyms is set 1
currently.
3.2 A Combined-Word Query
We consider the case in which a query contains several words combined with boolean AND / OR. The result ofAND searches are generally smaller than that of each word in the queries, and that of OR searches are oppositely
larger than that of each word. Hence we express the suitability of an AND / OR search as follows.

[3] http://www.altavista.com/[4] http://www.yahoo.com/[5] http://infoseek.go.com/[6] http://www.doginfo.com/[7] http://www.biocrawler.com/[8] http://lawcrawler.findlaw.com/[9] http://www.iijnet.or.jp/edr/index.html

AND search The suitability is calculated as the geometric mean of every pimps,w for every w in the query q:ps,q =

pimp
s,w

1
 |q|

(4)

w∈q

OR search The suitability is calculated as the average value of every pimps,w for every w in the query q:
ps,q =4impw∈q ps,w|q|(5)

Ranking Web Pages from the Search Engines

For obtaining a single hit list, MetaWeaver ranks Web pages in hit lists to order them. MetaWeaver employs thesuitability of each search engine and hit ranking of each Web pages in the hit list from each engine for the singlelist.
A score σ(p) of a Web page p expresses as follows:
σ(p) =

 ps,qk(p)
ap(6)

s∈S

where Sap is appropriate (query-requested) search engines, k(p) is the ranking of the page p in a hit list from asearch engine.
Here, the top page of the list obtains 1 and the 10th page obtains 10. If a search engine s does not have p in theps,qis zero.
list, k(p)5Experiments

We made experiments to evaluate the effectiveness of using suitability in MetaWeaver. To simplify the experiments,
we do not employ thesaurus for the improvement of the suitability, and the word and hits database has alreadystored randomly 2000 words in the thesaurus and their hits. Also the queries for a evaluation in the experiment are‘dna’, ‘soccer’ as single-word queries, ‘golden AND retriever’ and ‘punitive AND law’ as combined-word queries.
We choose 100 for the correction factor f s that is the history of hits from the word and hits database and 10 for α u .
Experimental results are shown in Table 1. In the table, “IS” means Infoseek, “AV” means AltaVista, “YH”
means Yahoo, “BC” means BioCrawler, “LC” means LawCrawler and “DI”means DogInfo. If MetaWeaver selects
correctly appropriate search engines, it will get right lists of ranking of search engines for each query. The lists aresorted largest first by the suitabilities of the search engines.
The results indicate our aiming tendency toward estimating specialty search engines’ suitabilities at the top.
The query ‘soccer’ does not have precise specialty search engines. Thus, no specialty search engine is the top andthe general search engines occupy the top three. The suitability of the top one or two is ten times larger than thatof below.

Ranking123
456

Table 1: The search engine ranking of the queries
dnasoccer
golden retriever
punitive law
SEpw
SEpw
SEpw
SEpw
BC 0.02336 AV 0.01317 DI0.11111 LC 0.00203
DI 0.01296 IS 0.00311 YH0.00026 AV 0.00015
LC 0.00715 YH 0.00285 AV
0.00018 YH 0.00000
AV 0.00346 LC 0.00148 IS0.00003 IS 0.00000
IS 0.00187 DI 0.00092 LC0.00000 DI 0.00000
YH 0.00047 BC 0.00000 BC0.00000 BC 0.00000

6Conclusion

Ordinary meta-search engines present too abundant Web pages over since they had submitted all of the registered search engines. Also specialty-sensitive meta-search engines like SavvySearch does not consider effect ofthesaurus. MetaWeaver solves both disadvantages. MetaWeaver selectively utilizes fewer search engines with asuitability.
In the experimental results, we confirm that the definition of the suitability is valid. We will use this system fora long time to investigate whether it adapt real person’s queries or not.

References
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Selberg, E. and Etzioni, O. (1997). The MetaCrawler Architecture for Resource Aggregation on the Web in both Postscript andHTML, IEEE Expert, 12 (1), 8–14.
Bharat, K. and Broder, A. (1998). A technique for measuring the relative size and overlap of Web search engines, Proceedingsof the 7th International World Wide Web Conference.
Lawrence, S. and Giles, C.L. (1998). Inquirus, the NECI meta search engine, Proceedings of the 7th International World WideWeb Conference.
Fan, Y. and Gauch, S. (1999). Adaptive Agents for Information Gathering from Multiple, Distributed Information Source,
Proceedings of 1999 AAAI Spring Symposium on Intelligent Agents in Cyberspace, 40–46.