JPH11312177A - Device for evaluating home page preference - Google Patents
Device for evaluating home page preferenceInfo
- Publication number
- JPH11312177A JPH11312177A JP10134516A JP13451698A JPH11312177A JP H11312177 A JPH11312177 A JP H11312177A JP 10134516 A JP10134516 A JP 10134516A JP 13451698 A JP13451698 A JP 13451698A JP H11312177 A JPH11312177 A JP H11312177A
- Authority
- JP
- Japan
- Prior art keywords
- preference
- homepage
- time
- home page
- degree
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Withdrawn
Links
- 238000011156 evaluation Methods 0.000 claims description 10
- 238000000034 method Methods 0.000 claims description 8
- 238000011002 quantification Methods 0.000 claims description 6
- 230000001174 ascending effect Effects 0.000 claims description 4
- 238000013500 data storage Methods 0.000 abstract description 5
- 238000010586 diagram Methods 0.000 description 8
- 238000004364 calculation method Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
Landscapes
- Information Transfer Between Computers (AREA)
- Computer And Data Communications (AREA)
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
Abstract
Description
【0001】[0001]
【発明の属する技術分野】本発明は、インターネット機
器のマン・マシンインタフェースをインテリジェンス化
するためにインターネット上のホームページに対するユ
ーザの嗜好を定量化するホームページ嗜好評価装置に関
する。BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a homepage preference evaluation apparatus for quantifying a user's preference for a homepage on the Internet in order to make a man-machine interface of an Internet device intelligent.
【0002】[0002]
【従来の技術】一般に、インターネット上のホームペー
ジをユーザが訪れた履歴データとして、ブラウザーの履
歴ファイルデータによりホームページのアドレス(UR
L:Uniform Resource Locator)と、訪れた日時と、履
歴データの有効期限とホームページの更新日時が記録さ
れる。なお、この種のブラウザーとしては、マイクロソ
フト社のインターネット・エクスプローラやネットスケ
ープ社のネットスケープ・ナビゲータが知られている。
従来、これらの履歴データは、URLのアルファベット
順、日時の昇順、降順に表示させることができる。2. Description of the Related Art Generally, a homepage address (UR) is used as history data of a user visiting a homepage on the Internet by using history file data of a browser.
L: Uniform Resource Locator), the date and time of visit, the expiration date of history data, and the date and time of update of the homepage. As this type of browser, Microsoft Internet Explorer and Netscape Navigator are known.
Conventionally, these pieces of history data can be displayed in alphabetical order of URL, in ascending order of date and time, and in descending order of date and time.
【0003】[0003]
【発明が解決しようとする課題】しかしながら、上記従
来例では、履歴データをURLのアルファベット順、日
時の昇順、降順に表示するので単にデータの羅列にすぎ
ず、ユーザの嗜好を定量化することができないという問
題点がある。However, in the above-mentioned conventional example, the history data is displayed in alphabetical order of URL, in ascending order of date and time, and in descending order of date and time. There is a problem that can not be.
【0004】本発明は上記従来例の問題点に鑑み、イン
ターネット上のホームページを訪れたユーザの嗜好を数
値化することができるホームページ嗜好評価装置を提供
することを目的とする。The present invention has been made in view of the above-mentioned problems of the prior art, and has as its object to provide a homepage preference evaluation device capable of quantifying the preference of a user who has visited a homepage on the Internet.
【0005】[0005]
【課題を解決するための手段】本発明は上記目的を達成
するために、ホームページを訪れた回数と滞在時間を最
近の訪問ほど嗜好度の強さが大きくなるように重み付け
するようにしたものである。すなわち本発明によれば、
ホームページを訪れた訪問日時と滞在時間を記憶する記
憶手段と、前記記憶手段に記憶されている訪問日時と滞
在時間に基づいて、所定期間内に訪れた訪問回数と滞在
時間を最近の訪問ほど嗜好度の強さが大きくなるように
重み付けすることによりホームページの嗜好度の強さを
数値として算出するホームページ嗜好度数値化手段と
を、有するホームページ嗜好評価装置が提供される。According to the present invention, in order to achieve the above object, the number of visits to a homepage and the length of stay are weighted such that the more recent visits, the greater the degree of preference. is there. That is, according to the present invention,
A storage unit for storing a visit date and time and a stay time of visiting the homepage; and, based on the visit date and time and the stay time stored in the storage unit, the number of visits and the stay time within a predetermined period are set so that the more recent visits have a preference. There is provided a homepage preference evaluation apparatus having a homepage preference degree quantifying means for calculating the degree of preference of the homepage as a numerical value by weighting the degree of the degree so as to increase the degree of the degree.
【0006】[0006]
【発明の実施の形態】以下、図面を参照して本発明の実
施の形態を説明する。図1は本発明に係るホームページ
嗜好評価装置の一実施形態を示すブロック図、図2は図
1のホームページ嗜好評価装置のPADを示す説明図、
図3は図2のホームページ処理を詳しく示す説明図、図
4は図3の訪問日処理を詳しく示す説明図である。Embodiments of the present invention will be described below with reference to the drawings. FIG. 1 is a block diagram showing an embodiment of a homepage preference evaluation device according to the present invention, FIG. 2 is an explanatory diagram showing a PAD of the homepage preference evaluation device of FIG.
FIG. 3 is an explanatory diagram showing the homepage process of FIG. 2 in detail, and FIG. 4 is an explanatory diagram showing the visit date process of FIG. 3 in detail.
【0007】図1において、ホームページ履歴データ記
憶部1にはクライアント(ユーザ)11がインターネッ
ト12を介してホームページを訪れた訪問日時と滞在時
間が記憶されている。ホームページ嗜好度数値化部2は
図2〜図4に示すように、ホームページ履歴データ記憶
部に記憶されている訪問日時と滞在時間に基づいて、所
定期間内に訪れた訪問回数と滞在時間を最近の訪問ほど
嗜好度の強さが大きくなるように重み付けすることによ
りホームページの嗜好度の強さを数値として算出する。
また、ホームページ嗜好度数値化部2はモデム3を介し
てインターネット12に接続される。[0007] In FIG. 1, a homepage history data storage unit 1 stores a visit date and a stay time when a client (user) 11 visits a homepage via the Internet 12. As shown in FIGS. 2 to 4, the homepage preference degree quantification unit 2 calculates the number of visits and the stay time within a predetermined period based on the visit date and time and the stay time stored in the homepage history data storage unit. The degree of preference of the homepage is calculated as a numerical value by weighting so that the degree of preference increases with the visit.
The homepage preference degree quantification unit 2 is connected to the Internet 12 via the modem 3.
【0008】図2はURLが示すページ番号pのホーム
ページに対するユーザの嗜好度Fpを演算する処理を示
している。まず、初期化を行い(ステップS1)、次い
でpページ目のホームページについて図3に詳しく示す
ホームページ処理を実行することによりページ番号pの
嗜好度Fpを演算する(ステップS2→S3)。次いで
嗜好度Fpをその昇順又は降順に並べ替え(ステップS
4)、次いでこの嗜好度Fpを出力する(ステップS
5)。FIG. 2 shows a process of calculating the user's preference level Fp for the home page of the page number p indicated by the URL. First, initialization is performed (step S1), and then a homepage process shown in detail in FIG. 3 is performed on the pth homepage to calculate a preference degree Fp of the page number p (step S2 → S3). Next, the preference degrees Fp are sorted in ascending or descending order (step S
4) Then, this preference level Fp is output (step S).
5).
【0009】ステップS3におけるホームページ処理で
は、図3に詳しく示す訪問日処理を実行することによ
り、嗜好度の計算期間であるM日間の内のm(=1〜
M)日目のページ番号pに対する、滞在時間(延べ訪問
時間)tmpから見た嗜好の強さftpと、全訪問回数Nmp
から見た嗜好の強さfNpを演算する(ステップS11〜
S13)。なお、1日は0時から24時までもよいが、
当日6時から翌日6時までのように、インターネットの
利用形態に応じて1日が24時間となるようにあらかじ
め決めればよい。次いでM日間分のftpとfNpをそれぞ
れ加算してFtpとFNpを演算し(ステップS14)、次
いでFtpとFNpの大小を判定し(ステップS15)、大
きい方をページ番号pの嗜好度Fpと決定する(ステッ
プS16、S17)。In the homepage process in step S3, by executing a visit date process shown in detail in FIG.
M) The strength of preference ftp as viewed from the stay time (total visit time) tmp for the page number p on the day, and the total number of visits Nmp
Of the preference fNp viewed from the user (steps S11 to S11)
S13). The day may be from 00:00 to 24:00,
From 6:00 on the day to 6:00 on the following day, the day may be determined in advance so that one day is 24 hours in accordance with the usage form of the Internet. Next, ftp and fNp for M days are respectively added to calculate Ftp and FNp (step S14), and then the magnitude of Ftp and FNp is determined (step S15), and the larger one is determined as the preference degree Fp of the page number p. (Steps S16 and S17).
【0010】ステップS13における訪問日処理では、
図4に詳しく示すようにn回目の滞在開始時刻をTsnmp
とし、滞在終了時刻をTenmpとしてその滞在時間(訪問
時間)tnmp tnmp=Tenmp−Tsnmp を演算し(ステップS21→S22)、次いでその日、
すなわちm日目の全訪問回数Nmpの延べ訪問時間tmpを
演算する(ステップS23)。次いで嗜好度計算期間
(M日間)において最近の訪問ほど嗜好度に対する影響
が大きくなるように、以下のように各日(m日目)の延
べ訪問時間tmpと全訪問回数Nmpに重みを乗算すること
により、各日の延べ訪問時間tmpから見た嗜好の強さf
tpと、各日の全訪問回数Nmpから見た嗜好の強さfNpを
演算する。 ftp(m)=α・W(m)・tmp fNp(m)=W(m)・NmpIn the visit date processing in step S13,
As shown in detail in FIG. 4, the n-th stay start time is set to Tsnmp
The stay end time is Tenmp, and the stay time (visit time) tnmp tnmp = Tenmp−Tsnmp is calculated (step S21 → S22), and then,
That is, the total visit time tmp of the total number of visits Nmp on the m-th day is calculated (step S23). Next, in the preference calculation period (M days), the total visit time tmp and the total number of visits Nmp are multiplied by weights as follows, so that the more recent visits have a greater effect on the preference, as described below. By this, the strength f of the preference as viewed from the total visit time tmp of each day f
tp and the strength fNp of the preference viewed from the total number of visits Nmp of each day are calculated. ftp (m) = α · W (m) · tmp fNp (m) = W (m) · Nmp
【0011】ここで、経過日数mに対する重みの関数を
W(m)とし、また、嗜好の強さが数値に正比例するも
のとすると、関数W(m)は経過日数mと共に増加す
る。また、αは各日の全訪問回数Nmpから見た嗜好の強
さfNpで、延べ訪問時間tmpから見た嗜好の強さftpを
正規化するための係数である。Here, assuming that the weighting function for the number of elapsed days m is W (m), and that the strength of the preference is directly proportional to the numerical value, the function W (m) increases with the number of elapsed days m. Α is a strength fNp of the preference viewed from the total number of visits Nmp of each day, and is a coefficient for normalizing the strength ftp of the preference viewed from the total visit time tmp.
【0012】したがって、訪問回数と滞在時間を最近の
訪問ほど嗜好度の強さが大きくなるように重み付けして
M日間分加算して、インターネット上のホームページを
訪れたユーザの嗜好を数値化するので、一過的な訪問を
削除して訪問回数が多いページと一回の訪問であっても
滞在時間が長いページを表示することができる。Therefore, the number of visits and the staying time are weighted so that the degree of preference increases as the number of visits increases, and M days are added, and the preference of a user who has visited a homepage on the Internet is quantified. In addition, a temporary visit can be deleted to display a page with a large number of visits and a page with a long stay time even with a single visit.
【0013】[0013]
【発明の効果】以上説明したように本発明によれば、ホ
ームページを訪れた回数と滞在時間を最近の訪問ほど嗜
好度の強さが大きくなるように重み付けするようにした
ので、インターネット上のホームページを訪れたユーザ
の嗜好を数値化することができる。As described above, according to the present invention, the number of visits to the homepage and the staying time are weighted so that the more recent visits, the greater the degree of preference becomes. Can be converted into numerical values of the user's preferences.
【図1】本発明に係るホームページ嗜好評価装置の一実
施形態を示すブロック図である。FIG. 1 is a block diagram showing an embodiment of a homepage preference evaluation device according to the present invention.
【図2】図1のホームページ嗜好評価装置のPADを示
す説明図である。FIG. 2 is an explanatory diagram showing a PAD of the homepage preference evaluation device of FIG. 1;
【図3】図2のホームページ処理を詳しく示す説明図で
ある。FIG. 3 is an explanatory diagram showing the home page processing of FIG. 2 in detail;
【図4】図3の訪問日処理を詳しく示す説明図である。FIG. 4 is an explanatory diagram showing a visit date process of FIG. 3 in detail;
1 ホームページ履歴データ記憶部(記憶手段) 2 ホームページ嗜好度数値化部(ホームページ嗜好度
数値化手段)1 Homepage history data storage unit (storage means) 2 Homepage preference degree quantification unit (homepage preference degree quantification means)
───────────────────────────────────────────────────── フロントページの続き (51)Int.Cl.6 識別記号 FI G06F 15/419 320 ──────────────────────────────────────────────────続 き Continued on the front page (51) Int.Cl. 6 Identification code FIG06F 15/419 320
Claims (3)
間を記憶する記憶手段と、 前記記憶手段に記憶されている訪問日時と滞在時間に基
づいて、所定期間内に訪れた訪問回数と滞在時間を最近
の訪問ほど嗜好度の強さが大きくなるように重み付けす
ることによりホームページの嗜好度の強さを数値として
算出するホームページ嗜好度数値化手段とを、 有するホームページ嗜好評価装置。1. A storage unit for storing a visit date and time and a stay time when a user visits a homepage, and based on the visit date and time and the stay time stored in the storage unit, the number of visits and the stay time during a predetermined period are determined. A homepage preference evaluation device comprising: a homepage preference degree quantifying unit that calculates the intensity of the preference degree of the homepage as a numerical value by weighting so that the strength of the preference degree increases as the number of recent visits increases.
滞在時間から見た嗜好の強さと訪問回数から見た嗜好の
強さを正規化して両者を比較し、大きい方をそのページ
の嗜好度の強さとして採用することを特徴とする請求項
1記載のホームページ嗜好評価装置。2. The homepage preference degree quantification means,
2. The method according to claim 1, wherein the strength of the preference viewed from the stay time and the strength of the preference viewed from the number of visits are normalized and compared, and the larger one is adopted as the strength of the preference of the page. Homepage preference evaluation device.
嗜好度の強さをホームページ毎に昇順又は降順に並べ替
えて出力することを特徴とする請求項1又は2記載のホ
ームページ嗜好評価装置。3. The homepage preference degree quantification means,
The homepage preference evaluation device according to claim 1 or 2, wherein the strength of preference is rearranged in ascending or descending order for each homepage and output.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| JP10134516A JPH11312177A (en) | 1998-04-28 | 1998-04-28 | Device for evaluating home page preference |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| JP10134516A JPH11312177A (en) | 1998-04-28 | 1998-04-28 | Device for evaluating home page preference |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| JPH11312177A true JPH11312177A (en) | 1999-11-09 |
Family
ID=15130163
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| JP10134516A Withdrawn JPH11312177A (en) | 1998-04-28 | 1998-04-28 | Device for evaluating home page preference |
Country Status (1)
| Country | Link |
|---|---|
| JP (1) | JPH11312177A (en) |
Cited By (18)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6321221B1 (en) | 1998-07-17 | 2001-11-20 | Net Perceptions, Inc. | System, method and article of manufacture for increasing the user value of recommendations |
| US6334127B1 (en) * | 1998-07-17 | 2001-12-25 | Net Perceptions, Inc. | System, method and article of manufacture for making serendipity-weighted recommendations to a user |
| JP2001357389A (en) * | 2000-06-12 | 2001-12-26 | Topcon Corp | Eyeglass frame selection service system and program recording medium therefor |
| KR20020003466A (en) * | 2000-07-04 | 2002-01-12 | 현영호 | Trading of Internet Web Site |
| KR20020022744A (en) * | 2002-02-25 | 2002-03-27 | 김일 | A disclination analysis system and method using internet navigation history list |
| WO2002046961A1 (en) * | 2000-12-06 | 2002-06-13 | Sony Corporation | Information processing device |
| US6412012B1 (en) | 1998-12-23 | 2002-06-25 | Net Perceptions, Inc. | System, method, and article of manufacture for making a compatibility-aware recommendations to a user |
| KR20030079095A (en) * | 2002-04-01 | 2003-10-10 | (주)메타웨이브 | Search system and method using web-page visiting history information of individual and group |
| KR100405220B1 (en) * | 2000-11-17 | 2003-11-12 | 주식회사 비즈모델라인 | Method and system for CRM by using automatic web page movement system |
| KR20030090052A (en) * | 2002-05-21 | 2003-11-28 | 이승환 | Analysis method for visitor use pattern in internet site |
| KR100411747B1 (en) * | 2000-07-12 | 2003-12-24 | 김시우 | The system for concluding search ranking and the method for concluding search ranking thereof |
| KR100509276B1 (en) * | 2001-08-20 | 2005-08-22 | 엔에이치엔(주) | Method for searching web page on popularity of visiting web pages and apparatus thereof |
| WO2005116857A1 (en) * | 2004-05-27 | 2005-12-08 | Nhn Corporation | Community search system through network and method thereof |
| KR100617662B1 (en) * | 2000-03-14 | 2006-08-28 | 엘지전자 주식회사 | How to configure and manage user history information of multimedia data and how to configure user profile information based on it |
| US7461058B1 (en) | 1999-09-24 | 2008-12-02 | Thalveg Data Flow Llc | Optimized rule based constraints for collaborative filtering systems |
| CN100462969C (en) * | 2006-08-29 | 2009-02-18 | 深圳市我炫网络科技有限公司 | Methods of using the Internet to provide and query information for the public |
| WO2010061990A1 (en) * | 2008-11-28 | 2010-06-03 | Estsoft Corp. | Web page searching system and method using access time and frequency |
| JP2017153637A (en) * | 2016-02-29 | 2017-09-07 | ハイライツ・エンタテインメント株式会社 | Advertisement information provision system |
-
1998
- 1998-04-28 JP JP10134516A patent/JPH11312177A/en not_active Withdrawn
Cited By (21)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6321221B1 (en) | 1998-07-17 | 2001-11-20 | Net Perceptions, Inc. | System, method and article of manufacture for increasing the user value of recommendations |
| US6334127B1 (en) * | 1998-07-17 | 2001-12-25 | Net Perceptions, Inc. | System, method and article of manufacture for making serendipity-weighted recommendations to a user |
| US6412012B1 (en) | 1998-12-23 | 2002-06-25 | Net Perceptions, Inc. | System, method, and article of manufacture for making a compatibility-aware recommendations to a user |
| US7461058B1 (en) | 1999-09-24 | 2008-12-02 | Thalveg Data Flow Llc | Optimized rule based constraints for collaborative filtering systems |
| KR100617662B1 (en) * | 2000-03-14 | 2006-08-28 | 엘지전자 주식회사 | How to configure and manage user history information of multimedia data and how to configure user profile information based on it |
| JP2001357389A (en) * | 2000-06-12 | 2001-12-26 | Topcon Corp | Eyeglass frame selection service system and program recording medium therefor |
| KR20020003466A (en) * | 2000-07-04 | 2002-01-12 | 현영호 | Trading of Internet Web Site |
| KR100411747B1 (en) * | 2000-07-12 | 2003-12-24 | 김시우 | The system for concluding search ranking and the method for concluding search ranking thereof |
| KR100405220B1 (en) * | 2000-11-17 | 2003-11-12 | 주식회사 비즈모델라인 | Method and system for CRM by using automatic web page movement system |
| US7599987B2 (en) | 2000-12-06 | 2009-10-06 | Sony Corporation | Information processing device for obtaining high-quality content |
| WO2002046961A1 (en) * | 2000-12-06 | 2002-06-13 | Sony Corporation | Information processing device |
| KR100853917B1 (en) * | 2000-12-06 | 2008-08-25 | 소니 가부시끼 가이샤 | Information processing apparatus and method, information processing system, and recording medium |
| KR100509276B1 (en) * | 2001-08-20 | 2005-08-22 | 엔에이치엔(주) | Method for searching web page on popularity of visiting web pages and apparatus thereof |
| KR20020022744A (en) * | 2002-02-25 | 2002-03-27 | 김일 | A disclination analysis system and method using internet navigation history list |
| KR20030079095A (en) * | 2002-04-01 | 2003-10-10 | (주)메타웨이브 | Search system and method using web-page visiting history information of individual and group |
| KR20030090052A (en) * | 2002-05-21 | 2003-11-28 | 이승환 | Analysis method for visitor use pattern in internet site |
| WO2005116857A1 (en) * | 2004-05-27 | 2005-12-08 | Nhn Corporation | Community search system through network and method thereof |
| US7761441B2 (en) | 2004-05-27 | 2010-07-20 | Nhn Corporation | Community search system through network and method thereof |
| CN100462969C (en) * | 2006-08-29 | 2009-02-18 | 深圳市我炫网络科技有限公司 | Methods of using the Internet to provide and query information for the public |
| WO2010061990A1 (en) * | 2008-11-28 | 2010-06-03 | Estsoft Corp. | Web page searching system and method using access time and frequency |
| JP2017153637A (en) * | 2016-02-29 | 2017-09-07 | ハイライツ・エンタテインメント株式会社 | Advertisement information provision system |
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