共查询到20条相似文献，搜索用时 31 毫秒
1.
《Information processing & management》2005,41(4):777-787
Latent Semantic Indexing (LSI) uses the singular value decomposition to reduce noisy dimensions and improve the performance of text retrieval systems. Preliminary results have shown modest improvements in retrieval accuracy and recall, but these have mainly explored small collections. In this paper we investigate text retrieval on a larger document collection (TREC) and focus on distribution of word norm (magnitude). Our results indicate the inadequacy of word representations in LSI space on large collections. We emphasize the query expansion interpretation of LSI and propose an LSI term normalization that achieves better performance on larger collections. 相似文献
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Concurrent concepts of specificity are discussed and differentiated from each other to investigate the relationship between index term specificity and users’ relevance judgments. The identified concepts are term-document specificity, hierarchical specificity, statement specificity, and posting specificity. Among them, term-document specificity, which is a relationship between an index term and the document indexed with the term, is regarded as a fruitful research area. In an experiment involving three searches with 175 retrieved documents from 356 matched index terms, the impact of specificity on relevance judgments is analyzed and found to be statistically significant. Implications for index practice and for future research are discussed. 相似文献
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Conventional information retrieval technology (i.e. VSM) faces many difficulties when being implemented in complex P2P systems for the lack of global statistic information (e.g. IDF) and central services. In this paper, we suggest a novel query optimization scheme (Semantic Dual Query Expansion, SDQE) that makes full use of the context information supplied by the local document collection. Latent Semantic Indexing (LSI) is used to explore the local context information. By comparing the different local context information hidden in different document collections, it is possible to solve the synonymy–polysemy problem in VSM. The experiments prove that our scheme is effective to improve the retrieval performance in P2P systems without knowing the global statistic information. 相似文献
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Fatemeh Lashkari Ebrahim Bagheri Ali A. Ghorbani 《Information processing & management》2019,56(3):733-755
Traditional information retrieval techniques that primarily rely on keyword-based linking of the query and document spaces face challenges such as the vocabulary mismatch problem where relevant documents to a given query might not be retrieved simply due to the use of different terminology for describing the same concepts. As such, semantic search techniques aim to address such limitations of keyword-based retrieval models by incorporating semantic information from standard knowledge bases such as Freebase and DBpedia. The literature has already shown that while the sole consideration of semantic information might not lead to improved retrieval performance over keyword-based search, their consideration enables the retrieval of a set of relevant documents that cannot be retrieved by keyword-based methods. As such, building indices that store and provide access to semantic information during the retrieval process is important. While the process for building and querying keyword-based indices is quite well understood, the incorporation of semantic information within search indices is still an open challenge. Existing work have proposed to build one unified index encompassing both textual and semantic information or to build separate yet integrated indices for each information type but they face limitations such as increased query process time. In this paper, we propose to use neural embeddings-based representations of term, semantic entity, semantic type and documents within the same embedding space to facilitate the development of a unified search index that would consist of these four information types. We perform experiments on standard and widely used document collections including Clueweb09-B and Robust04 to evaluate our proposed indexing strategy from both effectiveness and efficiency perspectives. Based on our experiments, we find that when neural embeddings are used to build inverted indices; hence relaxing the requirement to explicitly observe the posting list key in the indexed document: (a) retrieval efficiency will increase compared to a standard inverted index, hence reduces the index size and query processing time, and (b) while retrieval efficiency, which is the main objective of an efficient indexing mechanism improves using our proposed method, retrieval effectiveness also retains competitive performance compared to the baseline in terms of retrieving a reasonable number of relevant documents from the indexed corpus. 相似文献
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El-Sayed Atlam Ghada ElmarhomyAuthor VitaeKazuhiro MoritaAuthor Vitae Masao FuketaAuthor VitaeJun-ichi AoeAuthor Vitae 《Information processing & management》2006
With increasing popularity of the Internet and tremendous amount of on-line text, automatic document classification is important for organizing huge amounts of data. Readers can know the subject of many document fields by reading only some specific Field Association (FA) words. Document fields can be decided efficiently if there are many FA words and if the frequency rate is high. This paper proposes a method for automatically building new FA words. A WWW search engine is used to extract FA word candidates from document corpora. New FA word candidates in each field are automatically compared with previously determined FA words. Then new FA words are appended to an FA word dictionary. From the experiential results, our new system can automatically appended around 44% of new FA words to the existence FA word dictionary. Moreover, the concentration ratio 0.9 is also effective for extracting relevant FA words that needed for the system design to build FA words automatically. 相似文献
7.
《Information processing & management》2001,37(4):571-591
Stochastic simulation has been very effective in many domains but never applied to the WWW. This study is a premiere in using neural networks in stochastic simulation of the number of rejected Web pages per search query. The evaluation of the quality of search engines should involve not only the resulting set of Web pages but also an estimate of the rejected set of Web pages. The iterative radial basis functions (RBF) neural network developed by Meghabghab and Nasr [Iterative RBF neural networks as meta-models for stochastic simulations, in: Second International Conference on Intelligent Processing and Manufacturing of Materials, IPMM’99, Honolulu, Hawaii, 1999, pp. 729–734] was adapted to the actual evaluation of the number of rejected Web pages on four search engines, i.e., Yahoo, Alta Vista, Google, and Northern Light. Nine input variables were selected for the simulation: (1) precision, (2) overlap, (3) response time, (4) coverage, (5) update frequency, (6) boolean logic, (7) truncation, (8) word and multi-word searching, (9) portion of the Web pages indexed. Typical stochastic simulation meta-modeling uses regression models in response surface methods. RBF becomes a natural target for such an attempt because they use a family of surfaces each of which naturally divides an input space into two regions X+ and X− and the n patterns for testing will be assigned either class X+ or X−. This technique divides the resulting set of responses to a query into accepted and rejected Web pages. To test the hypothesis that the evaluation of any search engine query should involve an estimate of the number of rejected Web pages as part of the evaluation, RBF meta-model was trained on 937 examples from a set of 9000 different simulation runs on the nine different input variables. Results show that two of the variables can be eliminated which include: response time and portion of the Web indexed without affecting evaluation results. Results show that the number of rejected Web pages for a specific set of search queries on these four engines very high. Also a goodness measure of a search engine for a given set of queries can be designed which is a function of the coverage of the search engine and the normalized age of a new document in result set for the query. This study concludes that unless search engine designers address the issue of rejected Web pages, indexing, and crawling, the usage of the Web as a research tool for academic and educational purposes will stay hindered. 相似文献
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Previous studies have repeatedly demonstrated that the relevance of a citing document is related to the number of times with which the source document is cited. Despite the ease with which electronic documents would permit the incorporation of this information into citation-based document search and retrieval systems, the possibilities of repeated citations remain untapped. Part of this under-utilization may be due to the fact that very little is known regarding the pattern of repeated citations in scholarly literature or how this pattern may vary as a function of journal, academic discipline or self-citation. The current research addresses these unanswered questions in order to facilitate the future incorporation of repeated citation information into document search and retrieval systems. Using data mining of electronic texts, the citation characteristics of nine different journals, covering the three different academic fields (economics, computing, and medicine & biology), were characterized. It was found that the frequency (f) with which a reference is cited N or more times within a document is consistent across the sampled journals and academic fields. Self-citation causes an increase in frequency, and this effect becomes more pronounced for large N. The objectivity, automatability, and insensitivity of repeated citations to journal and discipline, present powerful opportunities for improving citation-based document search. 相似文献
10.
Document length normalization is one of the fundamental components in a retrieval model because term frequencies can readily be increased in long documents. The key hypotheses in literature regarding document length normalization are the verbosity and scope hypotheses, which imply that document length normalization should consider the distinguishing effects of verbosity and scope on term frequencies. In this article, we extend these hypotheses in a pseudo-relevance feedback setting by assuming the verbosity hypothesis on the feedback query model, which states that the verbosity of an expanded query should not be high. Furthermore, we postulate the following two effects of document verbosity on a feedback query model that easily and typically holds in modern pseudo-relevance feedback methods: 1) the verbosity-preserving effect: the query verbosity of a feedback query model is determined by feedback document verbosities; 2) the verbosity-sensitive effect: highly verbose documents more significantly and unfairly affect the resulting query model than normal documents do. By considering these effects, we propose verbosity normalized pseudo-relevance feedback, which is straightforwardly obtained by replacing original term frequencies with their verbosity-normalized term frequencies in the pseudo-relevance feedback method. The results of the experiments performed on three standard TREC collections show that the proposed verbosity normalized pseudo-relevance feedback consistently provides statistically significant improvements over conventional methods, under the settings of the relevance model and latent concept expansion. 相似文献
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《Information processing & management》2003,39(1):117-131
The inverted file is the most popular indexing mechanism for document search in an information retrieval system. Compressing an inverted file can greatly improve document search rate. Traditionally, the d-gap technique is used in the inverted file compression by replacing document identifiers with usually much smaller gap values. However, fluctuating gap values cannot be efficiently compressed by some well-known prefix-free codes. To smoothen and reduce the gap values, we propose a document-identifier reassignment algorithm. This reassignment is based on a similarity factor between documents. We generate a reassignment order for all documents according to the similarity to reassign closer identifiers to the documents having closer relationships. Simulation results show that the average gap values of sample inverted files can be reduced by 30%, and the compression rate of d-gapped inverted file with prefix-free codes can be improved by 15%. 相似文献
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In this paper, we propose a new algorithm, which incorporates the relationships of concept-based thesauri into the document categorization using the k-NN classifier (k-NN). k-NN is one of the most popular document categorization methods because it shows relatively good performance in spite of its simplicity. However, it significantly degrades precision when ambiguity arises, i.e., when there exist more than one candidate category to which a document can be assigned. To remedy the drawback, we employ concept-based thesauri in the categorization. Employing the thesaurus entails structuring categories into hierarchies, since their structure needs to be conformed to that of the thesaurus for capturing relationships between categories. By referencing various relationships in the thesaurus corresponding to the structured categories, k-NN can be prominently improved, removing the ambiguity. In this paper, we first perform the document categorization by using k-NN and then employ the relationships to reduce the ambiguity. Experimental results show that this method improves the precision of k-NN up to 13.86% without compromising its recall. 相似文献
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Sequences of integers are common data types, occurring either as primary data or ancillary structures. The sizes of sequences can be large, making compression an interesting option. Effective compression presupposes variable-length coding, which destroys the regular alignment of values. Yet it would often be desirable to access only a small subset of the entries, either by position (ordinal number) or by content (element value), without having to decode most of the sequence from the start. Here such a random access technique for compressed integers is described, with the special feature that no auxiliary index is needed. The solution applies a method called interpolative coding, which is one of the most efficient non-statistical codes for integers. Indexing is avoided by address calculation guaranteeing sufficient space for codes even in the worst case. The additional redundancy, compared to regular interpolative coding, is only about 1 bit per source integer for uniform distribution. The time complexity of random access is logarithmic with respect to the source size for both position-based and content-based retrieval. According to experiments, random access is faster than full decoding when the number of accessed integers is not more than approximately 0.75 · n/log2n for sequence length n. The tests also confirm that the method is quite competitive with other approaches to random access coding, suggested in the literature. 相似文献
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《Information processing & management》2005,41(4):745-758
Document filtering (DF) and document classification (DC) are often integrated together to classify suitable documents into suitable categories. A popular way to achieve integrated DF and DC is to associate each category with a threshold. A document d may be classified into a category c only if its degree of acceptance (DOA) with respect to c is higher than the threshold of c. Therefore, tuning a proper threshold for each category is essential. A threshold that is too high (low) may mislead the classifier to reject (accept) too many documents. Unfortunately, thresholding is often based on the classifier's DOA estimations, which cannot always be reliable, due to two common phenomena: (1) the DOA estimations made by the classifier cannot always be correct, and (2) not all documents may be classified without any controversy. Unreliable estimations are actually noises that may mislead the thresholding process. In this paper, we present an adaptive and parameter-free technique AS4T to sample reliable DOA estimations for thresholding. AS4T operates by adapting to the classifier's status, without needing to define any parameters. Experimental results show that, by helping to derive more proper thresholds, AS4T may guide various classifiers to achieve significantly better and more stable performances under different circumstances. The contributions are of practical significance for real-world integrated DF and DC. 相似文献
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《Information processing & management》2002,38(6):743-748
An interpolation theorem for the p-norm model, 1⩽p⩽∞, of Salton, Fox, and Wu for extended Boolean document retrieval is stated and proven. This result asserts roughly that whenever two or more documents are similarly ranked at any two points along the p-continuum with respect to this model for either an AND or an OR query containing exactly two terms, then they are similarly ranked at all points in between. An analogous result can fail for queries with more than two terms and an example is given to show this. 相似文献
17.
CBMdisc主题标引一致性的探讨 总被引：7，自引：0，他引：7
通过一个发表在两种不同期刊上的同一文献在CBMdisc中标引不一致的例子，分析了造成主题标引不一致的原因，并就减少这种主题标引不一致提出了几点建议。 相似文献
18.
A new model for aggregating multiple criteria evaluations for relevance assessment is proposed. An Information Retrieval context is considered, where relevance is modeled as a multidimensional property of documents. The usefulness and effectiveness of such a model are demonstrated by means of a case study on personalized Information Retrieval with multi-criteria relevance. The following criteria are considered to estimate document relevance: aboutness, coverage, appropriateness, and reliability. 相似文献
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The article discusses two instant measures of affective value of information objects: Willingness-to-Pay (WTP) and Experienced Utility (EU). The potential utility of these measures for information retrieval research is positioned within a broader discussion of distinctions between instant utility and remembered utility and their relationship to immediate as opposed to retrospective subjective evaluations. The paper describes an approach for obtaining instant WTP and EU ratings in document evaluation in contexts of information search and thereafter reports results from a usability study of its implementation. Participants encountered no difficulties in use of the design format and in rating documents using WTP and EU measures. Although two measures were found statistically significantly correlated with each other, participants in the usability study offered different reasons for the ratings of WTP and EU made for the same document. 相似文献
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《Information processing & management》2005,41(3):549-568
This paper presents a Foreign-Language Search Assistant that uses noun phrases as fundamental units for document translation and query formulation, translation and refinement. The system (a) supports the foreign-language document selection task providing a cross-language indicative summary based on noun phrase translations, and (b) supports query formulation and refinement using the information displayed in the cross-language document summaries. Our results challenge two implicit assumptions in most of cross-language Information Retrieval research: first, that once documents in the target language are found, Machine Translation is the optimal way of informing the user about their contents; and second, that in an interactive setting the optimal way of formulating and refining the query is helping the user to choose appropriate translations for the query terms. 相似文献