M. Morita and Y. Shinoda. Information filtering based on user behavior analysis and best match text retrieval. In Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval, pages 272--281. Springer-Verlag New York, Inc., 1994.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....relevance to a user s query can be gathered passively rather than actively, then users can experience the benefits of relevance feedback without having to expend any additional effort. Implicit feedback techniques have been primarily investigated in information filtering and recommendation systems [2, 3, 5, 7]. Behaviors most extensively investigated as sources for implicit feedback have been reading, saving and printing. For instance, 5] found that the major factor influencing the amount of time a user spends with a news article is the user s preference for that article. Specifically, 5] found that ....

....having to expend any additional effort. Implicit feedback techniques have been primarily investigated in information filtering and recommendation systems [2, 3, 5, 7] Behaviors most extensively investigated as sources for implicit feedback have been reading, saving and printing. For instance, [5] found that the major factor influencing the amount of time a user spends with a news article is the user s preference for that article. Specifically, 5] found that there is a strong tendency for users to spend a greater length of time reading those articles rated as interesting, as opposed to ....

[Article contains additional citation context not shown here]

Morita, M., & Shinoda, Y. (1996). Information filtering based on user behavior analysis and best match text retrieval. Proceedings of the 17 Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 272-281.

....has been posted. In his study, Stevens [20] observed that implicit feedback is effective in tracking longterm interests because it operates constantly without being intrusive. Morita and Shinoda proposed a profile processing technique to collect users preferences based on reading time monitoring [21]. Their research showed a strong, positive correlation between the reading time and the explicit ratings provided by testers. The Refer group has focuses on the correlations between users Web browsing actions (implicit interests) and their explicit interests [22] They built a Web browser called ....

....or ignoring, reading time, and mouse actions) Two approaches are usually used in text filtering. One is to map reading or ignoring into explicit ratings with rate 1 representing reading and 0 representing ignoring, the other is to map the time spent on reading into explicit ratings [21, 22]. In our system, we use the implicit ratings with reading as 1 and ignoring as 0. The only difference between the filtering systems using explicit and implicit feedback is the way they collect ratings. Otherwise, they can use the same collaborative technologies to provide predictions. Because ....

Morita, M. and Shinoda, Y. (1994), Information Filtering Based on User Behavior Analysis and Best Match Text Retrieval, Proceedings of the 17th ACM Annual International Conference on Research and Development in Information Retrieval (SIGIR'94), Dublin, Ireland, SpringerVerlag, 272-281.

....the Hyperdoc engine. User modelling and adaptive systems often employ explicit modelling where users are questioned on their preferences before interacting with the system. While this provides a high level of detail about the user, explicit modelling is often seen as time consuming and intrusive [13, 15]. The alternative technique, implicit modelling, obtains user preferences through observations of the users activities as they interact with the system [2] However implicit modelling provides only positive exemplars of user actions and requires both lengthy user interaction and the ability to ....

M Morita and Y. Shinoda. Information filtering based on user behavior analysis and best match text retrieval. In Proceedings of the Seventeenth Annual International ACM-SIGIR Conference on Research and Development in Information Retrieval, pages 272--281, 1994.

....IF. 1.1. 2 Approaches to Information filtering Information filtering techniques have been applied to several application areas including scientific publications [Luh58] technical memos and reports [FD92, FC97] Usenet news [FS91, Bac91, SK92, Ste92b, Bac92, JH92, SM93, Mae94, KHL 94, RIS 94, MS94, Lan95, YG95, Moc96, MRK97, MRK 97] electronic mail [Mye80, MGT 87, Pol88, GNOT92, Ter91, Ter93, LMM94] books [Ric79b, MR98] application program know how [LN98] the finding of experts [SW93, KSS96] Web pages [RM96, HT96, Bal97, THA 97, PB97, RP97, Bie98] classified ads [GGKS95] movies ....

.... usually means effort to users, attempts to use multi dimensional ratings have failed so far [KRBH98] Ratings may be provided explicitly, e.g. by selecting a rating from a pull down menu or by pressing a numeric key, or implicitly by monitoring user activities, e.g. reading time of news messages [MS94] or the saving of an object for later use [Nic97, AZ97, Bal98] Similar information may also be gathered in an offline manner by mining objects containing usage data. Examples for such systems are the Referral Web [KSS97a, KSS97b, KS98] that mines publicly available documents to build a model of ....

[Article contains additional citation context not shown here]

M. Morita and Y. Shinoda. Information filtering based on user behavior analysis and best match text retrieval. In Proceedings of the 17th Annual International Retrieval, pages 272-281, Dublin, Ireland, July 1994. ACM, New

.... GET toc.html HTTP 1.0 200 2540 From these entries, time spent on each page can be calculated. The longer a user spent on a page, the likelier the user is interested in the page. If a page is not interesting, a user usually jumps to another page quickly. Experimental studies in [25, 19] confirm this observation. However, a quick jump might be caused by the short length of the page, hence the user s interest might be more appropriately approximated by the time spent on a page normalized by the page s length. We note that activities other than surfing the web (e.g. answering a ....

M. Morita and Y. Shinoda. Information filtering based on user behavior analysis and best match text retrieval. In Proc. SIGIR-94, pages 272--281, 1994.

....user links all or part of an item into another item. They suggest two strategies for using implicit ratings. Our work proposes to experimentally evaluate one of their two strategies using implicit ratings from one of the three categories proposed. 2. 2 Experiments on Examining Morita and Shinoda [12] study the amount of time spent reading a Usenet News article. They examined users in a carefully controlled experimental environment in which users were not allowed to interrupt their reading and only read a carefully chosen news domain. They nd that the time people spend reading Net News ....

....spent reading an article and the explicit ratings. They could obtain substantially more ratings by using implicit ratings, and predictions based on time spent reading are nearly as accurate as predictions based on explicit ratings. They also provide con rmation of the results of Morita and Shinoda [12]. Our work seeks to extend their experiments into alternative domains, as well as to greatly expand the number of implicit ratings examined. Goecks and Shavlik [3] measure browsing activity in an attempt to predict the future activity of the user. They modify Microsoft s Internet Explorer to ....

[Article contains additional citation context not shown here]

M. Morita and Y. Shinoda. Information Filtering Based on User Behavior Analysis and Best Match Text Retrieval. In Proceedings of SIGIR Conference on Research and Development, pages 272 - 281, 1994.

....structure to be discovered. When these measures are applied to determine the similarity between a query and a document, they serve in matching or ranking. In this section we adapt two similarity measures used in IR to share information among InfoAgents in the Caf e, the substring indexing method [24] and the Cosine measure method [25] For more information, see [33] 6.4.2.1. Substring Indexing Substring indexing is simply the proportion of common terms in two documents (or InfoAgents) It is expressed as follows. Let a i represent i th agent and K (a i ) represent the set of keyphrases ....

Morita, M. and Y. Shinoda: 1994, `Information Filtering Based on User Behavior Analysis and Best Match Text Retrieval'. In: Proceeedings of the Seventeenth Annual International ACM-SIGIR Conference on Research and Development in Information Retrieval. pp. 272-281.

....document within that collection could be taken to be valuable for that user. The second set of judgment metadata ideas involves identifying observable user behaviors that are effective predictors of user interest. One predictor is the time a user spends studying a particular document. One study [29] shows that time spent reading a particular netnews article is indeed a good indicator of interest. It further shows that time not spent is a good indicator of disinterest. Finally, the study suggests that interest or disinterest in a piece of information is a good predictor for levels of interest ....

M. Morita and Y. Shinoda. Information filtering based on user behavior analysis and best match text retrieval. In Proceedings of the Seventeenth Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 1994.

....provided, at least in part because providing feedback takes time and may increase the cognitive load on the user. Implicit feedback, in which the system learns by observing the user s behavior, offers an attractive alternative that has received increased attention in recent years (Stevens, 1993; Morita Shinoda, 1994; Konstan et al. 1997; Nichols, 1997; Oard Kim, 1998; Kim et al., 2000) This study seeks to provide a practical basis for user modeling for information filtering based on implicit feedback. In the next section, we briefly describe prior work on the use of implicit feedback in information ....

....message was read or ignored, whether it was saved or deleted, and whether or not a follow up message was posted. In summarizing this groundbreaking study, Stevens observed that implicit feedback was effective for tracking long term interests because it operates constantly without being intrusive. Morita and Shinoda (1994) introduced another source, proposing an information filtering technique based on observations of reading time. They conducted user study over a six week period with eight users to determine whether preference for Internet discussion group USENET messages was reflected in the time spent reading ....

[Article contains additional citation context not shown here]

Morita, M and Shinoda, Y. (1994) Information filtering based on user behavior analysis and best match text retrieval. Proceedings of the Seventeenth Annual International ACM-SIGIR Conference on Research and Development in Information Retrieval, pp. 272-281.

....implicit feedback. In the explicit relevance feedback, the users rate all articles according to their relevance. In the implicit, the users read articles by performing scrolling and enlarging the articles, and the system infers from the behaviors how much the user was interested in each article. [Morita and Shinoda, 1994] exploited a heuristic, which uses behavior monitoring to capture the user s interests in information, for filtering the news articles. They have determined whether a user is interested in an article or not by measuring the time to read it. MAXIMS [Lashkari et al. 1994] classifies the stream of ....

Morita, M. and Shinoda, Y. 1994. Information filtering based on user behavior analysis and best match text retrieval, In Proc. ACM SIGIR Conf. on Research and Development in Information Retrieval (SIGIR-94), pp. 272-281.

....according to the user pro le. While they show some preliminary evaluation of their approach to user recommendations, they do not directly analyze the correlation between their implicit measure of user interest and the users explicit interest. 2.4. 2 Experiments on Examining Morita and Shinoda [16] study the amount of time spent reading a Usenet News article. They examined users in a carefully controlled experimental environment in which users were not allowed to interrupt their reading and only read a carefully chosen news domain. They nd that the time people spend reading Usenet News ....

....or attribution: for review purposes only. 7 could obtain substantially more ratings by using implicit ratings, and predictions based on time spent reading are nearly as accurate as predictions based on explicit ratings. They also provide con rmation of the results of Morita and Shinoda [16]. Our work seeks to extend their experiments into alternative domains, as well as to greatly expand the number of implicit ratings examined. Goecks and Shavlik [8] measure browsing activity in an attempt to predict the future activity of the user. They modify Microsoft s Internet Explorer to ....

[Article contains additional citation context not shown here]

M. Morita and Y. Shinoda. Information Filtering Based on User Behavior Analysis and Best Match Text Retrieval. In Proceedings of SIGIR Conference on Research and Development, pages 272 - 281, 1994.

....feedback, since this would take time away from their tasks. Implicit feedback, inferred on the basis of user behavior, offers the potential to reduce this cognitive load. It is thus a natural source to consider when constructing an implicit user model for text filtering systems (Stevens, 1993; Morita Shinoda, 1994; Konstan et al. 1997; Nichols, 1997; Oard Kim, 1998) Powerize Server, developed by powerize.com, is a content based text retrieval and filtering system that searches multiple internal and external information sources simultaneously and presents the retrieved documents to the user in a ....

....that are measured should, of course, be both easily observed and useful as sources of insight into a user s preferences. Previous studies on Internet discussion groups (USENET news) have found that predictions based on reading time can be about as accurate as those based on explicit ratings (Morita Shinoda, 1994; Konstan et al., 1997) In this report we describe the results of experiments that examined: i) whether reading time is also useful for predicting explicit ratings for academic or professional journal articles, and ii) whether retention behavior adds anything to what we already know from reading ....

[Article contains additional citation context not shown here]

Morita, M and Shinoda, Y. (1994) Information filtering based on user behavior analysis and best match text retrieval. Proceedings of the Seventeenth Annual International ACM-SIGIR Conference on Research and Development in Information Retrieval, pp. 272-281.

....based on time spent reading are nearly as accurate as predictions based on explicit numerical ratings. Figure 6 shows an analysis of the relationship between time spend reading and explicit ratings. Our results also provide large scale confirmation of the work of Morita and Shinoda [7] in finding the relationship between time and rating holds true without regard for the length of the article. We are continuing to explore further implicit ratings 84 March 1997 Vol. 40, No. 3 COMMUNICATIONS OF THE ACM Figure 7. GroupLens server architecture. The beige box encloses the ....

Morita, M. and Shinoda, Y. Information filtering based on user behavior analysis and best match text retrieval. In Proceedings of SIGIR '94. ACM, New York.

....On the other hand, the selection of a document by the user also does not necessarily mean that it is interesting for him. Therefore, some noise reduction of the selected objects is necessary for extracting only those ones that are really interesting. The results from experiments by Morita and Shinoda (1994) and Konstan et al. 1997) show that the time spent on reading is highly correlated with users explicit rating of interestingness of articles. This correlation may be not very strong for some domains. Nevertheless, a suitable threshold for the time spent for reading will be able to set apart the ....

Morita M., Shinoda Y. (1994), Information Filtering Based on User Behavior Analysis and Best Match Text Retrieval. In proceedings of SIGIR' 94. ACM, New York.

....cost and processing time at low levels. The IR literature offers a wide collection of techniques, models and algorithms that can be embodied in the structure of an IR system. The Vector Space Model (VSM) is today the most widely and commonly used representation model in the domains of IR [5] [6]. It is established as an effective and efficient retrieval model and many IR applications use it to represent information and calculate results, in an IR schema. In the application developed in this project, the information objects of location features and hotel properties as well as user ....

Masahiro Morita, Yoichi Shinoda, "Information Filtering Based on User Behavior Analysis and Best Match Text Retrieval", FIGIR, Special Interest Group on Information Retreival, pages 272281, 1994 .

....provided, at least in part because providing feedback takes time and may increase the cognitive load on the user. Implicit feedback, in which the system learns by observing the user s behavior, offers an attractive alternative that has received increased attention in recent years (Stevens, 1993; Morita Shinoda, 1994; Konstan et al. 1997; Nichols, 1997; Oard Kim, 1998; Kim et al., 2000) In the next section, we review the state of the art on the use of implicit feedback in information access systems, drawing together what has evolved over time as a diverse set of fields to assemble a coherent picture of the ....

....message was read or ignored, whether it was saved or deleted, and whether or not a follow up message was posted. In summarizing this groundbreaking study, Stevens observed that implicit feedback was effective for tracking long term interests because it operates constantly without being intrusive. Morita and Shinoda (1994) introduced another source, proposing an information filtering technique based on observations of reading time. They conducted user study over a six week period with eight users to determine whether preference for Internet discussion group USENET messages was reflected in the time spent reading ....

[Article contains additional citation context not shown here]

Morita, M and Shinoda, Y. (1994) Information filtering based on user behavior analysis and best match text retrieval. Proceedings of the Seventeenth Annual International ACM-SIGIR Conference on Research and Development in Information Retrieval, pp. 272-281.

....and mobile phones. Our system uses the access log and thus no extra load is put on the user for the construction of the collaborative filter. Infoscope (Stevens 1992) uses a similar assumption when the reading time for USENET news articles serve as a basis for collaborative filtering. Moreover, Morita and Shinoda (1994) show in a study, also of USENET news, that the reading time measurement actually produced better recall and precision in a text filtering experiment than using documents explicitly rated by the user as interesting. Other approaches such as matching profiles provide users with new resources ....

Morita, M. and Y. Shinoda (1994) "Information Filtering Based on User Behavior Analysis and Best Match Text Retrieval," In Proceedings of the 17th International ACM-SIGIR Conference on Research and Development in Information Retrieval. Dublin, Ireland, 272--281.

....user links all or part of an item into another item. They suggest two strategies for using implicit ratings. Our work proposes to experimentally evaluate one of their two strategies using implicit ratings from one of the three categories proposed. 2. 2 Experiments on Examining Morita and Shinoda [MS94] study the amount of time spent reading a Usenet News article. They examined users in a carefully controlled experimental environment in which users were not allowed to interrupt their reading and only read a carefully chosen news domain. They find that the time people spend reading Net News ....

....reading an article and the explicit ratings. They could obtain substantially more ratings by using implicit ratings, and predictions based on time spent reading are nearly as accurate as predictions based on explicit ratings. They also provide confirmation of the results of Morita and Shinoda [MS94] Our work seeks to extend their experiments into alternative domains, as well as to greatly expand the number of implicit ratings examined. Goecks and Shavlik [GS99] measure browsing activity in an attempt to predict the future activity of the user. They modify Microsoft s Internet Explorer to ....

[Article contains additional citation context not shown here]

M. Morita and Y. Shinoda. Information Filtering Based on User Behavior Analysis and Best Match Text Retrieval. In Proceedings of SIGIR Conference on Research and Development, pages 272 -- 281, 1994.

....9 [24] is different from the previous approaches in that it allows for implicit rating and is an exclusively collaborative filtering system. Information sources: Quality assessments of articles are based on explicit feedback and the time a user spent on a page (an approach also investigated in [37, 39, 41] and, with some modifications, implemented in this thesis. This quality assessment technique issue is discussed in some depth in chapter 3. Collaborative vs. individual: GroupLens is not suited for individual personalization (and can therefore be seen as a recommendation service as discussed ....

M. Morita and Y. Shinoda. Information filtering based on user behavior analysis and best match text retrieval. In Proc. 17th Annual Intl. ACMSIGIR Conf. on Research and Development in Information Retrieval, pages 272--281, 1994.

.... GET toc.html HTTP 1.0 200 2540 From these entries, time spent on each page can be calculated. The longer a user spent on a page, the likelier the user is interested in the page. If a page is not interesting, a user usually jumps to another page quickly. Experimental studies in [15, 11] confirm this observation. However, a quick jump might be caused by the short length of the page, hence the user s interest might be more appropriately approximated by the time spent on a page normalized by the page s length. We note that activities other than surfing the web (e.g. answering a ....

M. Morita and Y. Shinoda. Information filtering based on user behavior analysis and best match text retrieval. In Proc. SIGIR-94, pages 272--281, 1994.

....where w x;t was the number of times term t occurred in document or query x. The Inverse Document Frequency has been implemented but was not used in these experiments since each query and document only contained a single article. 3 Sub String Indexing This similarity measure (Morita and Shinoda [MS94]) is simply the proportion of common terms in the document and the query: sim = 2 j V q V d j j V q j j V d j : 4 Experiments A sample of articles consisting of 101 articles was taken in non sequential order from a newsgroup with a number of ongoing threads and heterogeneous postings ....

M. Morita and Y. Shinoda. Information filtering based on user behavior analysis and best match text retrieval. In Proceedings of the Seventeenth Annual International ACM-SIGIR Conference on Research and Development in Information Retrieval, pages 272--281. Springer-Verlag, 1994.

....into our framework by adopting the perspective that queries are information objects in their own right. user s interests. USENET newsreader software typically records the identifiers of messages that users have seen, and Karlgren (1994) explored the design of a recommender system using such lists. Morita and Shinoda (1994) and Konstan et al. 1997) found a positive correlation between reading time and explicit ratings in USENET news applications, and we have generalized that source of observations as examination duration to accommodate other modalities such as audio and video. Hill et al. 1992) have developed ....

Morita, M. and Shinoda, Y. 1994. Information Filtering Based on User Behavior Analysis and Best Match Text Retrieval. In Proceedings of the Seventeenth Annual International ACM-SIGIR Conference on Research and Development in Information Retrieval, 272-281.

....approach for our experiments because it allows for straightforward implementation and it suits our evaluation methodology well. In the future, adaptive text filtering systems will likely also exploit the sort of over the shoulder observations of user behavior investigated by Morita and Shinoda [Mori94]. Regardless of the approach chosen, present adaptive text filtering systems are most effective when used to satisfy relatively stable and specific information needs because a substantial quantity of consistent training data can be accumulated over time. By multilingual text filtering systems, ....

Masahiro Morita and Yoichi Shinoda. Information filtering based on user behavior analysis and best match text retrieval. In W. Bruce Croft and C.J. van Rijsbergen, editors, ACM SIGIR-94 Conference Proceedings, pages 272--281. Springer-Verlag, July 1994. http://shinoda-www.jaist.ac.jp:8000/papers/1994/sigir-94.ps.

....scale. Or it could be implicit feedback, where inferences are made from observations of readers actions, for instance as they use software to browse through or read recommended documents. In typical scenarios users will supply explicit feedback only grudgingly as Morita and Shinoda point out (Morita Shinoda 1996), it is unreasonable to impose extra load onto users already trying to mitigate their information overload. Therefore the first goal is to learn to recommend appropriate documents using only implicit feedback. Affording users control over the composition of their recommendation sets Perhaps a ....

Morita, M., and Shinoda, Y. 1996. Information filtering based on user behavior analysis and best match text retrieval. In Proceedings of the 19 th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 272--281.

....for articles he she reads, and to compute the weights of keywords from the score [Lang 95] Mock] This method also requires user s conscious involvement which is often annoying. A more subtle way is to consider the time that the user spent on each article, as in prior work based on Internet News [Morita 94] which is said to have worked fairly well. Unfortunately they insisted that subjects devote their entire concentration to the task of reading the article and not take breaks, which is not a very realistic solution. In The Krakatoa Chronicle, we included some of these method (typing explicit ....

Masahiro Morita and Yoichi Shinoda, Information Filtering Based on User Behavior Analysis and Best Match Text Retrieval, SIGIR'94, 1994

....where w x;t was the number of times term t occurred in document or query x. The Inverse Document Frequency has been implemented but was not used in these experiments since each query and document only contained a single article. 3 Sub String Indexing This similarity measure (Morita and Shinoda [MS94]) is simply the proportion of common terms in the document and the query: sim = 2 j V q V d j j V q j j V d j : 4 Experiments A sample of articles consisting of 101 articles was taken in non sequential order from a newsgroup with a number of ongoing threads and heterogeneous postings ....

M. Morita and Y. Shinoda. Information filtering based on user behavior analysis and best match text retrieval. In Proceedings of the Seventeenth Annual International ACM-SIGIR Conference on Research and Development in Information Retrieval, pages 272--281. Springer-Verlag, 1994.

....Each query corresponds to a topic the user is interested in. The document collection at any time, is the stream of unread messages provided by the subscribed newsgroups. This view has earlier been presented by Belkin and Croft [1] Our work is similar to that of Sheth [9] Morita and Shinoda [6], and Yan and Garcia Molina [11] Like them, we have decided to use a simple statistical similarity measure for queries and documents. We have evaluated two such measures, the well known cosine measure (Salton [8] and sub string indexing (Morita and Shinoda [6] However, we also want to take ....

....of Sheth [9] Morita and Shinoda [6] and Yan and Garcia Molina [11] Like them, we have decided to use a simple statistical similarity measure for queries and documents. We have evaluated two such measures, the well known cosine measure (Salton [8] and sub string indexing (Morita and Shinoda [6]) However, we also want to take advantage of the structural information contained in each message. We believe that a message filter (in contrast to an information filter) should be able to gain discriminative power from the physical appearence of a message. In quantitative terms: the amount of ....

M. Morita and Y. Shinoda. Information filtering based on user behavior analysis and best match text retrieval. In Proceedings of the Seventeenth Annual International ACM-SIGIR Conference on Research and Development in Information Retrieval, pages 272--281. Springer-Verlag, 1994.

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M. Morita and Y. Shinoda. Information filtering based on user behavior analysis and best match text retrieval. In Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval, pages 272--281. Springer-Verlag New York, Inc., 1994.

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Morita, M. and Shinoda, Y. (1994). Information filtering based on user behavior analysis and best match text retrieval. In Proceedings of SIGIR `94, 272-281.

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M. Morita and Y. Shinoda. Information filtering based on user behavior analysis and best match text retrieval. In SIGIR '94: Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval, pages 272--281, New York, NY, USA, 1994. Springer-Verlag New York, Inc.

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Morita, M and Shinoda, Y, 1994, Information filtering based on user behavior analysis and best match text retrieval. In Proceedings of the 17th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 272--281.

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Morita, M., & Shinoda, Y. (1994). Information filtering based on user behavior analysis and best match text retrieval. In Proceedings of SIGIR '94 (pp. 272--281). Dublin, Ireland: ACM Press.

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Masahiro Morita and Yoichi Shinoda. 1994. Information filtering based on user behavior analysis and best match text retrieval. In Proceedings of the 17th ACM SIGIR conference.

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Morita, M., Shinoda, Y. (1994): Information Filtering Based on User Behavior Analysis and Best Match Text Retrieval. Proceedings of the 17th Annual International SIGIR Conference on Research and Development. pp. 272--281

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Morita, M. and Shinoda, Y. Information filtering based on user behavior analysis and best match text retrieval, in Proceedings of SIGIR'94 (Dublin Ireland, July 1994), 272-281.

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Morita, M., Shinoda, Y.: Information filtering based on user behavior analysis and best match text retrieval. Proc. of the 17th Annual International Retrieval. Dublin, Ireland (1994)

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Morita, M. and Shinoda, Y. Information filtering based on user behavior analysis and best match text retrieval. Proceedings of the 17th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR `94) Dublin, Ireland. 3-6 July (1994)

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Morita, M., & Shinoda, Y. (1994). Information filtering based on user behavior analysis and best match text retrieval. In Proceedings of SIGIR '94, (pp. 272-281). Dublin, Ireland. ACM Press.

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Morita, M. & Shinoda, Y. (1994). Information filtering based on user behavior analysis and best match text retrieval. In Proceedings SIGIR, (Dublin, Ireland, July, 1994), ACM, 272281.

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Morita, M. and Shinoda, Y. Information Filtering Based on User Behavior Analysis and Best Match Text Retrieval, In Proceedings of the Seventeenth Annual International ACM-SIGIR Conference on Research and Development in Information Retrieval, pp.272-281, Springer-Verlag, 1994.

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Masahiro Morita and Yoichi Shinoda, Information Filtering Based on User Behavior Analysis and Best Match Text Retrieval, SIGIR'94, 1994

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