internet search engine freshness by web server help presented by: barilari alessandro

Internet Search Engine freshness by Web Server help

Presented by:

Barilari Alessandro

Mining di Dati Web Alessandro Barilari2

Introduction

Search engines are an important source of information and keeping them up-to-date will result in more accurate answers to search queries.

Search engines create their databases by probing web servers on a per-URL basis with a little help from the web servers.


Main Problem

There are no standard for facilitating the push of updates from servers to search engines:– It takes up to six months for a few page to be

indexed by popular web search engines;– The data which is indexed by the search engines

is often stale.


Solution…

Web server help to facilitate search engine freshness results in a favorable situation for web sites, search engines and users.


…and its problems

The number of updates per second is very large.

Must balance between:– The number of interactions between web sites

and search engines, and– The freshness of the search engines.


Page rank impact

Pages which are popular will have higher page ranks:– Use popularity in addition to age and freshness to

compute the mismatch between a web site and a search engine


Summary

Definitions and Cost Model Algorithm Analysis Pratical issues


Some definitions

Update: an update u to a file f is a modification to f that has been flushed to the disk;

Propagation of an update: an update is said to be propagate when the web site has informed the search engine about the update. A SE may or may not retrieve that update;

Meta-update propagation: At any time t, let U(t) be the set of unpropagated updates. The web site informs the search engine about all the updates U(t);


Some definitions (2)

Weight of a file: given a content file, its weight f (non-negative) denotes the importance of the file; the weights are chosen such that:

Last_modification_time(u,t): the last time before t when the file f(u) was updated.

1Ff

f


The Cost Model

Components:– Communication cost;– Opportunity cost: represents the stalenes of the

search engine data as compared to the data on the web server.

CPU cost is ignored


Opportunity cost (OC)

Given an unpropagated update u to a content file f; the opportunity cost for update u at time t is:

OC(u,t)=f(u)x(t - last_modification_time(u,t))

Definition for meta-update propagation:

tUu

tuOCttotOC ,_


Communication cost (CC)

sizef(u)(t): the size of file f(u) at time t;

t.before propagatedbeen not hasu if 0

t,before propagatedbeen hasu if 1,

,,

tu

tutsizektuCC uf


Potential Communication cost (PCC)

Represents the communication cost which would need to be incurred in case update u were to be propagated after time t:

tUu

uf

tuPCCttotPCC

tutsizektuPCC

,_

,1,


The Cost Function

Given that an update u is unpropagated at time t, the cost function for that update at time t is given by:

ttotCCttotOCttotCost

tuOCtuCCtuCost

___

,,,


Summary

Definition and Cost Model

Algorithm Analysis Pratical issues


FreshFlow Algorithm

When OC_tot equals PCC_tot at any time t, the web server can inform the search engine

about all the unpropagated updates.


Summary

Definition and Cost Model Algorithm

Analysis Pratical issues


Analysis

The cost of the FreshFlow algorithm (called FF) is compared with the cost of an optimal off-line algorithm (called ADV)


Analysis (2)

Lemma (1): OC(u,t) is monotonically non-decreasing;

Lemma (2): suppose an update u to a file f, and suppose FF transmits but ADV does not. Then OCADV(u,t)≥OCFF(u,t).

Lemma (3): if the update is transmitted by the adversary (ADV), then CCADV(u,t) ≥CCFF(u,t).


Theorem

FF is 2-competitive:

CostFF(u,t) ≤ 2 x CostADV(u,t)


Summary

Definition and Cost Model Algorithm Analysis

Pratical issues


Pratical issues

There are multiple search engines:– Synchronization effect: pushing the updates

would put pressure on the last-hop link to the web server;

– Search engine load: some search engines might deny the receipt of updates.


The middleman approach

Each web server contacts only one middleman for sending its updates;

Could be a group of middlemen.


Benefits

The middleman can solve some additional issues:– Verifying trustworthiness of web servers;– Restricting the rate at which updates get

transmitted to search engines;


Limitations

The algorithm has not been used in practice; The search engines need the cooperation of

the web servers to keep track of updates to their URLs. Whether web servers will incorporate such a service remains to be seen.


Conclusions

The FreshFlow algorithm is a solution that improve the data updates of the search engines, mantaining high level efficiency and performance;

The authors are planning to implement the algorithm in a real system (and have a future pubblication!)

internet search engine freshness by web server help presented by: barilari alessandro

Documents

dati webalessandro barilari

search engine slide

barilari alessandro

adv slide

cost ff u

cost adv u

time t

popular web search engines