OpenRaiser/Intern-Atlas huggingface dataset:
Interactive Internet search: keyword, directory and query reformulation mechanisms compared
Authors: Peter Bruza, Robert McArthur, Simon Dennis
Venue: SIGIR
Year: 2000

This article compares search effectiveness when using query-based Internet search (via the Google search engine), directory-based search (via Yahoo) and phrase-based query reformulation assisted search (via the Hyperindex browser) by means of a controlled, user-based experimental study. The focus was to evaluate aspects of the search process. Cognitive load was measured using a secondary digit-monitoring task to quantify the effort of the user in various search states; independent relevance judgements were employed to gauge the quality of the documents accessed during the search process. Time was monitored in various search states. Results indicated the directory-based search does not offer increased relevance over the query-based search (with or without query formulation assistance), and also takes longer. Query reformulation does significantly improve the relevance of the documents through which the user must trawl versus standard query-based internet search. However, the improvement in document relevance comes at the cost of increased search time and increased cognitive load.
Auto-construction of a live thesaurus from search term logs for interactive Web search
Authors: Shui-Lung Chuang, Hsiao-Tieh Pu, Wen-Hsiang Lu, Lee-Feng Chien
Venue: SIGIR
Year: 2000

The purpose of this paper is to present an on-going research that is intended to construct a live thesaurus directly from search term logs of real-world search engines. Such a thesaurus designed can contain representative search terms, their frequency in use, the corresponding subject categories, the associated and relevant terms, and the hot visiting Web sites/pages the search terms may reach.
Evaluation of a simple and effective music information retrieval method
Authors: J. Stephen Downie, Michael J. Nelson
Venue: SIGIR
Year: 2000

We developed, and then evaluated, a music information retrieval (MIR) system based upon the intervals found within the melodies of a collection of 9354 folksongs. The songs were converted to an interval-only representation of monophonic melodies and then fragmented t into length-n subsections called n-grams. The length of these n-grams and the degree to which we precisely represent the intervals are variables analyzed in this paper. We constructed a collection of &quot;musical word&quot; databases using the text-based, SMART information retrieval system. A group of simulated queries, some of which contained simulated errors, was run against these databases. The results were evaluated using the normalized precision and normalized recall measures. Our concept of &quot;musical words&quot; shows great merit thus implying that useful MIR systems can be constructed simply and efficiently using pre-existing text-based information retrieval software. Second, this study is a formal and comprehensive evaluation of ...
The effect of query type on subject searching behavior of image databases: an exploratory study
Authors: Efthimis N. Efthimiadis, Raya Fidel
Venue: SIGIR
Year: 2000

Article Free Access Share on The effect of query type on subject searching behavior of image databases (poster session): an exploratory study Authors: Efthimis N. Efthimiadis School of Library & Information Science, University of Washington, Box 352930, Seattle, WA School of Library & Information Science, University of Washington, Box 352930, Seattle, WAView Profile , Raya Fidel School of Library & Information Science, University of Washington, Box 352930, Seattle, WA School of Library & Information Science, University of Washington, Box 352930, Seattle, WAView Profile Authors Info & Claims SIGIR '00: Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrievalJuly 2000Pages 328–330https://doi.org/10.1145/345508.345625Published:01 July 2000Publication History 6citation17DownloadsMetricsTotal Citations6Total Downloads17Last 12 Months3Last 6 weeks0 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF
SWAMI: a framework for collaborative filtering algorithm development and evaluation
Authors: Danyel Fisher, Kris Hildrum, Jason I. Hong, Mark W. Newman, Megan Thomas, Rich Vuduc
Venue: SIGIR
Year: 2000

We present a Java-based framework, SWAMI (Shared Wisdom through the Amalgamation of Many Interpretations) for building and studying collaborative filtering systems. SWAMI consists of three components: a prediction engine, an evaluation system, and a visualization component. The prediction engine provides a common interface for implementing different prediction algorithms. The evaluation system provides a standardized testing methodology and metrics for analyzing the accuracy and run-time performance of prediction algorithms. The visualization component suggests how graphical representations can inform the development and analysis of prediction algorithms. We demonstrate SWAMI on the Each Movie data set by comparing three prediction algorithms: a traditional Pearson correlation-based method, support vector machines, and a new accurate and scalable correlation-based method based on clustering techniques.
Word document density and relevance scoring
Authors: Martin Franz, J. Scott McCarley
Venue: SIGIR
Year: 2000

Previous work addressing the issue of word distribution in documents has shown the importance of Word repetitiveness as an indicator of the word content-bearing characteristics. In this paper we propose a simple method using a measure of the tendency of words to repeat within a document to separate the words with similar document frequencies, but different topic discriminating characteristics. We describe the application of the new measure in query-document relevance scoring. Experiments on the TREC Ad Hoc and Spoken Document Retrieval tasks [7] show useful performance improvements.
Event tracking based on domain dependency
Authors: Fumiyo Fukumoto, Yoshimi Suzuki
Venue: SIGIR
Year: 2000

This paper proposes a method for event tracking on broadcast news stories based on distinction between a topic and an event. A topic and an event are identified using a simple criterion called domain dependency of words: how greatly a word features a given set of data. The method was tested on the TDT corpus which has been developed by the TDT Pilot Study and the result can be regarded as promising the usefulness of the method.
Do batch and user evaluation give the same results?
Authors: William R. Hersh, Andrew Turpin, Susan Price, Benjamin Chan, Dale Kraemer, Lynetta Sacherek, Daniel Olson
Venue: SIGIR
Year: 2000

Do improvements in system performance demonstrated by batch evaluations confer the same benefit for real users? We carried out experiments designed to investigate this question. After identifying a weighting scheme that gave maximum improvement over the baseline in a non-interactive evaluation, we used it with real users searching on an instance recall task. Our results showed the weighting scheme giving beneficial results in batch studies did not do so with real users. Further analysis did identify other factors predictive of instance recall, including number of documents saved by the user, document recall, and number of documents seen by the user.
Document filtering method using non-relevant information profile
Authors: Keiichiro Hoashi, Kazunori Matsumoto, Naomi Inoue, Kazuo Hashimoto
Venue: SIGIR
Year: 2000

Document filtering is a task to retrieve documents relevant to a user's profile from a flow of documents. Generally, filtering systems calculate the similarity between the profile and each incoming document, and retrieve documents with similarity higher than a threshold. However, many systems set a relatively high threshold to reduce retrieval of non-relevant documents, which results in the ignorance of many relevant documents. In this paper, we propose the use of a non-relevant information profile to reduce the mistaken retrieval of non-relevant documents. Results from experiments show that this filter has successfully rejected a sufficient number of non-relevant documents, resulting in an improvement of filtering performance.
Finding relevant passages using noun-noun compounds: coherence vs. proximity
Authors: Eduard Hoenkamp, Rob de Groot
Venue: SIGIR
Year: 2000

Intuitively, words forming phrases are a more precise description of content than words as a sequence of keywords. Yet, evidence that phrases would be more effective for information retrieval is inconclusive. This paper isolates a neglected class of phrases, that is abundant in communication, has an established theoretical foundation, and shows promise for an effective expression of the user's information need: the noun-noun compound (NNC). In an experiment, a variety of meaningful NNCs were used to isolate relevant passages in a large and varied corpus. In a first pass, passages were retrieved based on textual proximity of the words or their semantic peers. A second pass retained only passages containing a syntactically coherent structure equivalent to the original NNC. This second pass showed a dramatic increase in precision. Preliminary results show the validity of our intuition about phrases in the special but very productive case of NNCs.
Learning probabilistic models of the Web
Authors: Thomas Hofmann
Venue: SIGIR
Year: 2000

In the World Wide Web, myriads of hyperlinks connect documents and pages to create an unprecedented, highly complex graph structure - the Web graph. This paper presents a novel approach to learning probabilistic models of the Web, which can be used to make reliable predictions about connectivity and information content of Web documents. The proposed method is a probabilistic dimension reduction technique which recasts and unites Latent Semantic Analysis and Kleinberg's Hubs-and-Authorities algorithm in a statistical setting.
Multimedia information retrieval from recorded presentations
Authors: Wolfgang Hürst, Rainer Müller, Christoph Mayer
Venue: SIGIR
Year: 2000

In presentation recording special effort is usually put into the automation of the production process, that is in automatically creating high quality data files without much or any need for manual recording and post-editing [5]. With the advent of such systems and their usage in classroom teaching, at conferences, etc., there is an increasing need for techniques and abilities which enable users to search in those documents and to localize some specific information. In this paper we describe how we integrated information retrieval techniques into the Authoring on the Fly (AOF) system, an approach for automatic presentation recording. We have chosen the AOF system for two reasons. On the one hand, it is a well-established way for presentation recording, used by various universities and institutions1. On the other hand it is general enough to illustrate typical problems and challenges a developer is facing when designing a system for information retrieval from multimedia data streams which occur in the presentation recording scenario.
Relevance reedback with a small number of relevance judgements: incremental relevance feedback vs. document clustering
Authors: Makoto Iwayama
Venue: SIGIR
Year: 2000

The use of incremental relevance feedback and document clustering were investigated in an relevance feedback environment in which the number of relevance judgements was quite small. Through experiments on the TREC collection, the incremental relevance feedback approach was found not to improve the overall search effectiveness. The clustering approach was found to be promising, although it sometimes over-focuses on a particular topic in a query and ignores the others. To overcome this problem, a query-biased clustering algorithm was developed and shown to be effective.
Information access for context-aware appliances
Authors: Gareth J. F. Jones, Peter J. Brown
Venue: SIGIR
Year: 2000

The emergence of networked context-aware mobile computing appliances potentially offers opportunities for remote access to huge online information resources. Information access in context-aware information appliances can utilize existing techniques developed for effective information retrieval and information filtering; however, practical physical and operational features of these devices and the availability of context information itself suggest that the document selection process should make use of this contextual data.
Stemming and its effects on TFIDF ranking
Authors: Mark Kantrowitz, Behrang Mohit, Vibhu O. Mittal
Venue: SIGIR
Year: 2000

Article Stemming and its effects on TFIDF ranking (poster session) Share on Authors: Mark Kantrowitz Just Research, 4616 Henry Street, Pittsburgh, PA Just Research, 4616 Henry Street, Pittsburgh, PAView Profile , Behrang Mohit School of Computer Science, Carnegie Mellon University, Pittsburgh, PA School of Computer Science, Carnegie Mellon University, Pittsburgh, PAView Profile , Vibhu Mittal School of Computer Science, Carnegie Mellon University, Pittsburgh, PA School of Computer Science, Carnegie Mellon University, Pittsburgh, PAView Profile Authors Info & Claims SIGIR '00: Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrievalJuly 2000 Pages 357–359https://doi.org/10.1145/345508.345650Online:01 July 2000Publication History 28citation101DownloadsMetricsTotal Citations28Total Downloads101Last 12 Months51Last 6 weeks6 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access
Text filtering by boosting naive bayes classifiers
Authors: Yu-Hwan Kim, Shang-Yoon Hahn, Byoung-Tak Zhang
Venue: SIGIR
Year: 2000

Several machine learning algorithms have recently been used for text categorization and filtering. In particular, boosting methods such as AdaBoost have shown good performance applied to real text data. However, most of existing boosting algorithms are based on classifiers that use binary-valued features. Thus, they do not fully make use of the weight information provided by standard term weighting methods. In this paper, we present a boosting-based learning method for text filtering that uses naive Bayes classifiers as a weak learner. The use of naive Bayes allows the boosting algorithm to utilize term frequency information while maintaining probabilistically accurate confidence ratio. Applied to TREC-7 and TREC-8 filtering track documents, the proposed method obtained a significant improvement in LF1, LF2, F1 and F3 measures compared to the best results submitted by other TREC entries.
Generation of user profiles for information filtering - research agenda
Authors: Tsvi Kuflik, Peretz Shoval
Venue: SIGIR
Year: 2000

In information filtering (IF) systems, user long-term needs we expressed as user profiles. The quality of a user profile has a major impact on the performance of IF systems. The focus of the proposed research is on the study of user profile generation and update. The paper introduces methods for user profile generation, and proposes a research agenda for their comparison and evaluation.
Partial collection replication versus caching for information retrieval systems
Authors: Zhihong Lu, Kathryn S. McKinley
Venue: SIGIR
Year: 2000

Abstract The explosion of content in distributed infer-marion retrieval (IR) systems requires new mechanisms to attain timely and accurate retrieval of unstructured text. In this paper, we compare two mechanisms to improve IR sys-tem performance: partial collection replication and caching. When queries have locality, both mechanisms return results more quickly than sending queries to the original collec-tion(s). Caches return results when queries exactly match a previous one. Partial replicas are a form of caching that return results when the IR technology determines the query is a good match. Caches are simpler and faster, but repli-cas can increase locality by detecting similarity between queries that are not exactly the same. We use real traces from THOMAS and Excite to measure query locality and similarity. With a very restrictive definition of query sim-ilarity, similarity improves query locality up to 15 % over exact match. We use a validated simulator to compare their performance, and find that even if the partial replica hit rate increases only 3 to 6%, it will outperform simple caching under a variety of configurations. A combined approach will probably yield the best performance.
Document classification on neural networks using only positive examples
Authors: Larry M. Manevitz, Malik Yousef
Venue: SIGIR
Year: 2000

In this paper, we show how a simple feed-forward neural network can be trained to filter documents when only positive information is available, and that this method seems to be superior to more standard methods, such as tf-idf retrieval based on an “average vector”. A novel experimental finding that retrieval is enhanced substantially in this context by carrying out a certain kind of uniform transformation (“Hadamard”) of the information prior to the training of the network.
Theme-based retrieval of Web news
Authors: Nuno Maria, Mário J. Silva
Venue: SIGIR
Year: 2000

We present our framework for classification of Web news, based on support vector machines, and some of the initial measurements of its accuracy.
On the design and evaluation of a multi-dimensional approach to information retrieval
Authors: M. Catherine McCabe, Jinho Lee, Abdur Chowdhury, David A. Grossman, Ophir Frieder
Venue: SIGIR
Year: 2000

We present a method of searching text collections that takes advantage of hierarchrical information within documents and integrates searches of structured and unstructured data. We show that Multidimensional databases (MDB), designed for accessing data along hierarchical dimensions, are effective for information retrieval. We demonstrate a method of using On-Line Analytic Processing (OLAP) techniques on a text collection. This combines traditional information retrieval and the slicing, dicing, drill-down, and roll-up of OLAP. We demonstrate use of a prototype for searching documents from the TREC collection.
Influence of speech recognition errors on topic detection
Authors: J. Scott McCarley, Martin Franz
Venue: SIGIR
Year: 2000

We investigate the effect of speech-recognition errors on a system for the unsupervised, nearly synchronous clustering of broadcast news stories, using the TDT (Topic Detection and Tracking) Corpora. Two questions are addressed: (1) Are speech recognition errors detrimental to the performance of the system? (2) Can a background collection of contemporaneous clean text improve performance? We investigate both the large-cluster and small-cluster limits.
Document centered approach to text normalization
Authors: Andrei Mikheev
Venue: SIGIR
Year: 2000

In this paper we present an approach to tackle three important problems of text normalization: sentence boundary disambiguation, disambiguation of capitalized words when they are used in positions where capitalization is expected, and identification of abbreviations. The main feature of our approach is that it uses a minimum of pre-built resources, instead dynamically inferring disambiguation clues from the entire document itself. This makes it domain independent, closely targeted to each individual document and portable to other languages. We thoroughly evaluated this approach on several corpora and it showed high accuracy.
The use of phrases from query texts in information retrieval
Authors: Masumi Narita, Yasushi Ogawa
Venue: SIGIR
Year: 2000

Article Free Access Share on The use of phrases from query texts in information retrieval (poster session) Authors: Masumi Narita Software Research Center, Ricoh Co., Ltd., 1-1-17 Koishikawa, Bunkyo-ku, Tokyo, Japan Software Research Center, Ricoh Co., Ltd., 1-1-17 Koishikawa, Bunkyo-ku, Tokyo, JapanView Profile , Yasushi Ogawa Software Research Center, Ricoh Co., Ltd., 1-1-17 Koishikawa, Bunkyo-ku, Tokyo, Japan Software Research Center, Ricoh Co., Ltd., 1-1-17 Koishikawa, Bunkyo-ku, Tokyo, JapanView Profile Authors Info & Claims SIGIR '00: Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrievalJuly 2000 Pages 318–320https://doi.org/10.1145/345508.345621Online:01 July 2000Publication History 11citation18DownloadsMetricsTotal Citations11Total Downloads18Last 12 Months2Last 6 weeks0 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF
Pseudo-frequency method: an efficient document ranking retrieval method for n-gram indexing
Authors: Yasushi Ogawa
Venue: SIGIR
Year: 2000

Although n-gram (n successive characters) indexing is widely used in retrieval systems for documents in Japanese and other Asian languages, it is difficult to process ranking retrieval efficiently using n-gram indexing. This is because frequency information for query words needs to be computed using indexed data since this information is not directly available from the n-gram index. To reduce processing costs, this paper proposes a pseudo-frequency method, which uses a word's estimated frequencies instead of precise ones. The results of experiments on NTCIR, a Japanese IR test collection, showed that the proposed method speeded up retrieval without degrading retrieval effectiveness.
A practical hypertext categorization method using links and incrementally available class information
Authors: Hyo-Jung Oh, Sung-Hyon Myaeng, Mann-Ho Lee
Venue: SIGIR
Year: 2000

As WWW grows at an increasing speed, a classifier targeted at hypertext has become in high demand. While document categorization is quite a mature, the issue of utilizing hypertext structure and hyperlinks has been relatively unexplored. In this paper, we propose a practical method for enhancing both the speed and the quality of hypertext categorization using hyperlinks. In comparison against a recently proposed technique that appears to be the only one of the kind, we obtained up to 18.5% of improvement in effectiveness while reducing the processing time dramatically. We attempt to explain through experiments what factors contribute to the improvement.
Ranking digital images using combination if evidences
Authors: Iadh Ounis
Venue: SIGIR
Year: 2000

Article Ranking digital images using combination of evidences (poster session) Share on Author: Iadh Ounis University of Glasgow, Glasgow G12 8QQ, Scotland University of Glasgow, Glasgow G12 8QQ, ScotlandView Profile Authors Info & Claims SIGIR '00: Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrievalJuly 2000 Pages 348–350https://doi.org/10.1145/345508.345643Online:01 July 2000Publication History 0citation12DownloadsMetricsTotal Citations0Total Downloads12Last 12 Months2Last 6 weeks0 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access