B.J. Jansen, A. Spink, J. Bateman, and T. Saracevic, "Real Life Information Retrieval: A Study of User Queries on the Web," Proc. SIGIR Forum, 1998.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....in a relatively small number of databases selected by this method. In Section 6, we will conduct experiments to evaluate the effectiveness of our method based on more rigorous measures. The proposition below shows that for any single term query (which constitutes about 30 of all Internet queries [12]) the local databases selected by the integrated representative are guaranteed to contain the m most similar documents in all databases with respect to the query when m r. PROPOSITION 2. For any single term query, if the number of documents desired by the user, m, is less than or equal to r ....

B. Jansen, A. Spink, J. Bateman, and T. Saracevic. Real Life Information Retrieval: A Study of User Queries on the Web. ACM SIGIR Forum, 32:1, 1998.

....nature of the Web users, the role of ranking becomes critical. It is common for Web search queries to have thousands or millions of results. On the other hand Web users do not have the time and patience to go through them to find the ones they are interested in. It has actually been documented [10, 46, 27] that most Web users do not look beyond the first page of results. Therefore, it is important for the ranking function to output the desired results within the top few pages, otherwise the search engine is rendered useless. Furthermore, the needs of the users when querying the Web are different ....

B. J. Jansen, A. Spink, J. Bateman, and T. Saracevic. Real life Information Retrieval: A study of user queries on the Web. ACM SIGIR Forum, 32:5--17, 1998.

....there is an acute need for search engine technology to help users exploit such an extremely valuable resource. In weighted Information Retrieval (IR) the number of retrieved documents is related to the number of appropriate search terms. Retrieval with short queries is typical in Web search [6], but it is much harder as compared to retrieval with long queries. This is because shorter queries often provide less information for retrieval. Modern IR systems therefore integrate thesaurus browsers. They help to find additional search terms [13] But the keywords used in short queries are not ....

Jansen B.J., Spink A., Bateman J. and Saracevic T.: Real Life Information Retrieval: A Study of User Queries on the Web, In SIGIR Forum, Vol. 31, pp. 5-17, 1988

....the Boolean logic underlying conventional web search engines. Unfortunately, a growing majority of people using search engines has. An analysis of query logs of the search engine Excite has shown that, in practice, only 9 of the queries contain Boolean operators or the modifiers and [5]. The latter two require that a query term must or must not be present in the searched pages. Although large web search engines like Google, Altavista and of course thousands of smaller sitespecific search facilities have the same superficial appearance, they tend to interpret queries with subtle ....

....page to be loaded before canceling the request. We will compare the results of two studies analyzing query log files of the large and popular search engines Altavista and Excite with the results of our analysis, since only few research papers dealing with user behavior in web searches exist. In [5] and [13] the authors have shown that the average number of words per query is very small, namely 2.35, interestingly the same in both studies. This indicates that most of the people searching for information on the Internet could improve the quality of the results by specifying more query terms. ....

B. J. Jansen, A. Spink, J. Bateman, and T. Saracevic. Real life information retrieval: A study of user queries on the web. SIGIR Forum, 32(1):5--17, 1998.

....results ranked by expected topical relevance. But only a small percentage of these pages may be of a specific interest. In Information Retrieval (IR) the number of retrieved documents is related to the number of appropriate search terms. Retrieval with short queries is typical in Web search [13], but it is much harder as compared to retrieval with long queries. This is because shorter queries often provide less information for retrieval. Modern IR systems therefore integrate thesaurus browsers to find additional search terms [24] However, the aim of the retrieval activity is not to ....

Jansen B.J., Spink A., Bateman J. and Saracevic T.: Real Life Information Retrieval: A Study of User Queries on the Web, In S1G1R Forum, Vol. 31, pp. 5-17, 1988

....challenging because of the pure magnitude of the data to be analyzed. See [26] for a survey. Web user behavior: Mining user query logs shows that web users exhibit a di erent query behavior than users of classical information retrieval systems. An analysis of di erent query logs is given in [22, 36]. Modeling: Di erent users asking the same query can widely disagree on the relevance of the answers. Thus, it is not possible to prove that certain ranking algorithms return relevant answers at the top. However, there has been some recent work on trying to nd appropriate models for clustering ....

B. J. Jansen, A. Spin, J. Bateman, and T. Saracevic. Real Life Information Retrieval: A Study of User Queries on the Web. SIGIR FORUM, 32 (1):5-17, 1998.

....the formation of an information need, the user must express this need as a query. A query may contain several query terms, where each term represents criteria for the target documents. Web search engine users generally do not provide detailed queries, with average queries containing 2. 4 terms [30]. If a user is looking for documents regarding petroleum refining on the Falkland Islands, they may express their information need as: Falkland Islands petrol While an expert user may have a better understanding of how the retrieval system works and thus express their query as: Falkland ....

JANSEN, B. J., SPINK, A., BATEMAN, J., AND SARACEVIC, T. Real life information retrieval: A study of user queries on the Web. ACM SIGIR Forum 32, 1 (1998), 5-- 17.

....the exact information he she requires. In particular, it is difficult for the user to represent the information needs by a few keywords. It is said that the average number of keywords inputted by a user to Excite (http: www.excite.com) one of the more popular retrieval sites on WWW, is 2. 35 [1]. Kitani et al. 2] considered that queries vary with respect to the amount of knowledge about concerned fields and compared the number of keywords used in a query against two cases: 1) Users have sufficient knowledge about concerned fields. 2) Users have insufficient knowledge about them. ....

Jansen, B. J., Spink, A., Bateman, J. and Saracevic, T. Real life information retrieval: A study of user queries on the web. S1G1R Forum, 1998, 32(1), pp. 5 -17.

....documents to proxies or clients has been studied for further performance improvement by utilizing user access patterns [5] 6] There are previous studies on search engine traces. Jasen et al. analyzed the Excite search engine trace to determine how users search the Web and what they search for [7]. Silverstein et al. analyzed the Altavista search engine trace [8] studying the interaction of terms within queries and presenting results of a correlation analysis of the log entries. Although these studies have not focused on caching search engine results, all of them suggest queries have ....

....queries Fig. 2. User query distribution according to the number of words in each query is short. Fig. 2 shows the query length distributions of the two traces. We can observe that most of the queries are fewer than five terms long. Overall, these results are consistent with those reported in [7] and [8] and thus are not surprising. III. QUERY LOCALITY AND ITS IMPLICATIONS As mentioned in Section II C, 32 to 42 of the queries in the trace are repeated queries, which suggests caching as a way to reduce server workload and network traffic. In this section, we focus on the study of ....

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B.J. Jansen, A. Spink, J. Bateman, and T. Saracevic, "Real life information retrieval: a study of user queries on the Web," in SIGIR Forum, Vol. 32. No. 1, 1998, pp. 5--17.

....the Web there has been a growing interest in the study of variety of topics in issues related to the use of the Web. However, to date there has been few studies of Web search users. At the beginning of 98, Kirsch presented some search statistics of Infoseek usage in [3] But the main studies are [1], developed by Jansen et al. and [2] developed by Silverstein et al. where they demonstrate that Web search users differ significantly from users of traditional Information Retrieval systems. On the first one, they study queries taken from the query logs of Excite and on the second one they ....

....that there is an important percentage of queries and subjects searched few times, probably because they are very specific. 3. 2 Analysis of individual queries It is clear that searches on the web tend to have many fewer search terms than searches in traditional information retrieval contexts [1]. In our research we have found that the average words per query is a bit smaller (1.63) that the values found by Jansen et al. and Silverstein et al. probably due to linguistic reasons of the Spanish language. With regard to the number of operators used in queries, in Table 2 we can find some ....

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B. Jansen, A. Spink, J. Bateman, T. Saracevic, "Real Life Information Retrieval: A Study Of User Queries On The Web". SIGIR FORUM Spring 98.

....of traditional Information Retrieval systems. The first study was performed by Kirsh who, at the beginning of 98, presented some search statistics of Infoseek usage in [3] A bit later, Jansen et al. presented a study of queries, sessions and searched terms obtained in the query logs of Excite [1]. Silverstein et al. examined a very large number of queries taken from Altavista logs in [2] studying not only the queries but also the correlations among them. In the present paper we have two main objectives. The first one is to confirm and research new differences between the Web users and ....

....Search terms and search strings incremental percentage, using first screen results queries With regard to the number of operators used in queries, in Table 6 we can find a summary. The main conclusion is that logic operators are little used in queries. Also, this under utilization is present in [1] and [2] and suggests that web users do not have the basic knowledge of Boolean logic. Table 6: Logic operators usage statistics, with only the first screen results queries Spanish AND operator: Y 4.164 AND operator 0.362 Spanish NOT operator: NO 0.024 NOT operator 0.0006 Spanish OR ....

B. Jansen, A. Spink, J. Bateman, T. Saracevic, "Real Life Information Retrieval: A Study Of User Queries On The Web". SIGIR FORUM Spring 98.

....documents to proxies or clients has also been studied for further performance improvement by utilizing user access patterns [4, 7] There are also studies of search engine traces. Jasen et al. analyzed the Excite search engine trace to determine how users search the Web and what they search for [6]. Silverstein et al. analyzed the Altavista search engine trace [13] studying the interaction of terms within queries and presenting results of a correlation analysis of the log entries. Although these studies have not focused on caching search engine results, all of them suggest queries have ....

....of more than one word, although the average query length is less than three terms, which is short. Figures 1 shows the query length distributions of the two traces. We can observe that most of the queries are less than five terms long. Overall, these results are consistent with those reported in [6] and [13] and thus are not surprising. 1 2 3 4 5 6 7 8 9 10 10 0 5 10 15 20 25 30 35 40 Number of words in a query ( Percentage of the queries 1 2 3 4 5 6 7 8 9 10 10 0 5 10 15 20 25 30 35 Number of words in a query ( Percentage of the queries (a)the Vivisimo ....

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B.J. Jansen, A. Spink, J. Bateman, and T. Saracevic. Real life information retrieval: a study of user queries on the Web. In SIGIR Forum, Vol. 32. No. 1, pages 5--17, 1998.

....described e.g. in [11] 8] and [7] In [14] a probabilistic framework for database selection is presented. It is difficult to guess automatically the knowledge domain from a few query terms especially when considering that most users tend to submit queries consisting only of single terms [9]. This requires the evaluation of domain specific knowledge provided by thesauri and ontologies. Other strategies apply the statistical analysis of co occurrence of terms from large numbers of documents to compute association weights indicating thematical correlations ( 6] 4] In our approach, ....

B. Jansen, A. Spink, J. Bateman, and T. Saracevic. Real life information retrieval: A study of user queries on the web. In SIGIR Forum (ACM Special Interest Group on Information Retrieval), volume 32 Number 1, pages 5--17, 1998.

....important feature of each Web page to detect when a page is visible or not. A possible inconvenience of this part of the user interface is the need to use a scrollbar to see all the selected results. But we have to take into account that a common user will visit a reduced number of Web pages. In [10] they show that 67 of users just perform one query and 58 of users don t access any results past the first page. This two statistics shows that most users choose very few results and so, they will not need to use the scrollbar to navigate through them. Finally, the navigation control is the ....

....the user s navigation. But we have to take into account that the remote cache is global to all users and that in Internet search engines and directories many searches are repeated, which implies that an important percentage of the Web pages required will already be stored in the remote cache (in [10] it is clear that a high percentage of search terms are the same, which leads to the same search results and therefore, to the same Web pages visited) Anyway, Internet search engines and directories usually have a high throughput in order to avoid congestion problems accessing their Web sites, ....

B. Jansen, A. Spink, J. Bateman, and T. Saracevic "Real life information retrieval: A study of user queries on the Web". ACM SIGIR Forum, 32(1):5--17, 1998.

....contains a wide variety of document types and languages. High linkage: on average, each document points to other 8 pages. Specific behavior: users provide short and not particularly well represented queries and it is estimated that 65 users only look at the first screen of the returned results [10]. Superimposed coding have been used in signature files for storing flat information, nevertheless in this paper we expose how superimposed codes can be used to store hierarchical information (not necessarily as a tree but as a directed acyclic graph) and the direct application of this codes to ....

Jansen, B., Spink, A., Bateman, J., Saracevic, T. Real Life Information Retrieval: A Study Of User Queries On The Web. ACM SIGIR Forum, 32(1):5-17, 1998.

....engines. Finally, the meta search engine merges the documents retrieved from the selected servers to a final result list and returns it to the user. The fifty queries used in the experiments are the TREC topics 301 350; the short query format is adopted since the web queries are usually short [9]. Each short TREC query contains 2.48 terms on average. Furthermore, since the number of returned documents is usually large for the web queries and the user often just browses a small number of them, the precision of the top documents is taken as the most basic performance criterion in our ....

B. J. Jansen, A. Spink, J. Bateman, and T. Saracevic. Real life information retrieval: A study of user queries on the Web. SIGIR Forum, 32(1):5--17, 1998.

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B.J. Jansen, A. Spink, J. Bateman, and T. Saracevic, "Real Life Information Retrieval: A Study of User Queries on the Web," Proc. SIGIR Forum, 1998.

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B. P. Jansen, A. Spink, J. Bateman, and T. Saracevic. Real life information retrieval: A study of user queries on the web. ACM SIGIR Forum, 32(1):5--17, Spring 1998.

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B. Jansen, A. Spink, J. Bateman, and T. Saracevic. Real life information retrieval:a study of user queries on the web. SIGIR Forum, Vol.32. No.1.pp. 5-17, 1998.

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JANSEN,B.J.,SPINK,A.,BATEMAN,J.,AND SARACE- VIC, T. Real life information retrieval: a study of user queries on the web. ACM SIGIR Forum 32, 1 (1998), 5--17.

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B. J. Jansen, A. Spink, J. Bateman, and T. Saracevic. Real life information retrieval: A study of user queries on the web. ACM SIGIR Forum, 32(1):5--17, 1998.

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Jansen, B., Spink, A., Bateman, J., Saracevic, T. Real Life Information Retrieval: A Study of User Queries on the Web. SIGIR Forum, Vol. 32, Num. 1, 1998, New York: ACM, 5-17.

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B.J. Jansen, A. Spink, J. Bateman, and T. Saracevic. Real life information retrieval: a study of user queries on the Web. In SIGIR Forum, Vol. 32. No. 1, pages 5--17, 1998.

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B. J. Jansen, A. Spink, J. Bateman, and T. Saracevic. Real life information retrieval: A study of user queries on the Web. SIGIR Forum, 32(1):5--17, 1998.

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Jansen, B., Spink, A., Bateman, J., Saracevic, T. (1998). Real Life Information Retrieval: A Study of User Queries on the Web, SIGIR Forum, Vol. 32, Num. 1, New York: ACM, 5-17.

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