第五講旅行2021年9月9日

2021年9月9日王漢生1TravelingDomestic

Travel

(Times)2021年9月9日王漢生2Domestic

Travel

Income2021年9月9日王漢生3Smart

TourismHotel31524Complain6SafetyPlace2021年9月9日王漢生6PlaceBaidu

Forecasting2021年9月9日王漢生8HotelAir

TicketPlanning2021年9月9日王漢生11SafetyAirticketFarecastEtzioni,

O.,

R.

Tuchinda,

C.

A.

Knoblock

and

A.

Yates(2003).

To

buy

or

not

to

buy:

mining

airfare

data

tominimize

ticket

purchase

price.

Proceedings

of

theninth

ACM

SIGKDD

international

conference

onKnowledge

discovery

and

data

mining,

ACM.Oren

EtzioniUniversity

of

WashingtonComputer

Science

&EngineeringDirector

of

Turing

CenterEtzioni,

O.,

R.

Tuchinda,

C.A.

Knoblock

and

A.

Yates

(2003).

To

buy

ornot

to

buy:

mining

airfare

data

to

minimize

ticketpurchase

price.

Proceedings

of

the

ninth

ACM

SIGKDD

international

conference

on

Knowledge

discovery

and

data

mining,ACM.FarecastFarecastFarecast2021年9月9日王漢生17FarecastFarecastFarecast11.5

Million

$May

2009Oren

Etzioni

:

Farecast

is

the

most

special

function

of

Bing.“So,

we

end

up

with

Bing

travel

as

a

thin

veneer

that

redirects

users

toKayak,

while

Google

innovates

with

G/flights,

which

I

now

useall

the

time,”

said

Etzioni.

“Google

1,

Bing

0.”Etzioni

&

FarecastGoogle/flights2021年9月9日王漢生22Kayak2021年9月9日王漢生23Qunar2021年9月9日王漢生24航旅縱橫2021年9月9日王漢生25HansonForecasting:

HotelManagementHotelsate?LessvacantRooms!Lowrice!LeasingPrice?Price?RPProblems?Leasing

Rate?LessvacantRooms!LowPrice!Price?Profit!LeasingRatePriceDateDemandHotelSize……GuidelineDataDescriptionA

Direct-sale

Store

in

BeijingBasic

StatisticsSample

Size:

81,000Number

of

Hotels:

4

(Direct-sale)

+127

(Franchise)Time

:

2013-10-01

~2015-09-30

（7

DaysMissing）DatasetDayHotelIDHotelNameHouseCountAveHousePriceLeaseRate2014/1/1100Hai

Dian

Franchise116206.580.63792014/1/2100Hai

Dian

Franchise116197.840.50002014/1/3100Hai

Dian

Franchise116212.480.57762014/1/4100Chao

Yang

Direct

Sale114199.720.6932014/1/5100Chao

Yang

Direct

Sale116177.110.49142014/1/6100Chao

Yang

Direct

Sale116166.910.57762014/1/7100Guo

Mao

Direct

Sale116186.000.61212014/1/8100Guo

Mao

Direct

Sale116184.000.81032014/1/9100Guo

Mao

Direct

Sale115196.750.5304Price

Time

Series:

Direct-salePrice

Time

Series:FranchiseLease

Rate

Time

Series：Direct

SaleLease

Rate

Time

Series：FranchiseSpring

FestivalBaidu

Index

Time

SeriesBaidu

index

of

HotelBaidu

Index

Time

SeriesSpring

FestivalA

Direct-sale

HotelPrice

Time

SeriesLease

Rate

Time

SeriesSpring

FestivalHistogram

of

PriceSD

=

121.4%

out

±3

SDVariationcould

belarge!Histogram

of

Lease

Rate53%

Lease

Rate<0.7Leasingrate

is

lowLease

Rate

&

PriceNegatively

correlatedLagLeaseRateLagBaidu

IndexPositively

correlatedLease

Rate

&

Weekday1.00.90.80.70.60.50.40.30.20.10.0Price

&

Weekday180160140120100806040200Lease

Rate

&

Month1.00.90.80.70.60.50.40.30.20.10.0Price

&

Month1801601401201008060402001.41.210.80.60.40.20Standardized

Leasing

RateStandardized

Average

PriceLease

Rate

&

Price1.210.80.60.40.201.4Lease

Rate

&

PriceStandardized

Leasing

RateStandardized

Average

PriceRegression: Y

=

log(LeaseRate)Labor’s

DaySpring

FestivalQing

MingDynamic

Pricing1.00.90.80.70.60.50.40.30.20.10.01

2

3

4

5

6

7

8

9

10

11

12Original

Leasing

RateOptimized

Leasing

RatePoint

of

InterestData

Cleaning21354Data

Table2021年9月9日56王漢生Distribution

of

Tourism

at

Different

POIsSummer

Palace

46%Fragrant

Hill

9%Distribution

of

Tourism

at

Different

POIsDistribution

of

Tourism

at

Dining

PlacesDistribution

of

Tourism

at

Dining

PlacesDistribution

of

Tourism

at

Shopping

PlacesDistribution

of

Tourism

at

Shopping

PlacesDistribution

of

Tourism

at

HotelsDistribution

of

Tourism

at

HotelsHomeworkBeijing

Area31,890

Users1,549POI60,613

Registered

RecordsObjective:

Where

do

Weibo

usersliketogo?Andwhen?HomeworkTime:

Accurate

Date

and

TimeYear:

Calendar

YearMonth:

Calendar

MonthDay:

Calendar

D