共查询到20条相似文献，搜索用时 31 毫秒
1.
Fernando Diaz 《Information Retrieval》2007,10(6):531-562
We adapt the cluster hypothesis for score-based information retrieval by claiming that closely related documents should have
similar scores. Given a retrieval from an arbitrary system, we describe an algorithm which directly optimizes this objective
by adjusting retrieval scores so that topically related documents receive similar scores. We refer to this process as score
regularization. Because score regularization operates on retrieval scores, regardless of their origin, we can apply the technique
to arbitrary initial retrieval rankings. Document rankings derived from regularized scores, when compared to rankings derived
from un-regularized scores, consistently and significantly result in improved performance given a variety of baseline retrieval
algorithms. We also present several proofs demonstrating that regularization generalizes methods such as pseudo-relevance
feedback, document expansion, and cluster-based retrieval. Because of these strong empirical and theoretical results, we argue
for the adoption of score regularization as general design principle or post-processing step for information retrieval systems.
相似文献
| Fernando DiazEmail: |
2.
Diego Reforgiato Recupero 《Information Retrieval》2007,10(6):563-579
Text document clustering provides an effective and intuitive navigation mechanism to organize a large amount of retrieval
results by grouping documents in a small number of meaningful classes. Many well-known methods of text clustering make use
of a long list of words as vector space which is often unsatisfactory for a couple of reasons: first, it keeps the dimensionality
of the data very high, and second, it ignores important relationships between terms like synonyms or antonyms. Our unsupervised
method solves both problems by using ANNIE and WordNet lexical categories and WordNet ontology in order to create a well structured
document vector space whose low dimensionality allows common clustering algorithms to perform well. For the clustering step
we have chosen the bisecting k-means and the Multipole tree, a modified version of the Antipole tree data structure for, respectively, their accuracy and
speed.
相似文献
| Diego Reforgiato RecuperoEmail: |
3.
Smoothing of document language models is critical in language modeling approaches to information retrieval. In this paper,
we present a novel way of smoothing document language models based on propagating term counts probabilistically in a graph
of documents. A key difference between our approach and previous approaches is that our smoothing algorithm can iteratively
propagate counts and achieve smoothing with remotely related documents. Evaluation results on several TREC data sets show that the proposed method significantly outperforms the
simple collection-based smoothing method. Compared with those other smoothing methods that also exploit local corpus structures,
our method is especially effective in improving precision in top-ranked documents through “filling in” missing query terms
in relevant documents, which is attractive since most users only pay attention to the top-ranked documents in search engine
applications.
相似文献
| ChengXiang ZhaiEmail: |
4.
Multilingual information retrieval is generally understood to mean the retrieval of relevant information in multiple target
languages in response to a user query in a single source language. In a multilingual federated search environment, different
information sources contain documents in different languages. A general search strategy in multilingual federated search environments
is to translate the user query to each language of the information sources and run a monolingual search in each information
source. It is then necessary to obtain a single ranked document list by merging the individual ranked lists from the information
sources that are in different languages. This is known as the results merging problem for multilingual information retrieval.
Previous research has shown that the simple approach of normalizing source-specific document scores is not effective. On the
other side, a more effective merging method was proposed to download and translate all retrieved documents into the source
language and generate the final ranked list by running a monolingual search in the search client. The latter method is more
effective but is associated with a large amount of online communication and computation costs. This paper proposes an effective
and efficient approach for the results merging task of multilingual ranked lists. Particularly, it downloads only a small
number of documents from the individual ranked lists of each user query to calculate comparable document scores by utilizing
both the query-based translation method and the document-based translation method. Then, query-specific and source-specific
transformation models can be trained for individual ranked lists by using the information of these downloaded documents. These
transformation models are used to estimate comparable document scores for all retrieved documents and thus the documents can
be sorted into a final ranked list. This merging approach is efficient as only a subset of the retrieved documents are downloaded
and translated online. Furthermore, an extensive set of experiments on the Cross-Language Evaluation Forum (CLEF) () data has demonstrated the effectiveness of the query-specific and source-specific results merging algorithm against other
alternatives. The new research in this paper proposes different variants of the query-specific and source-specific results
merging algorithm with different transformation models. This paper also provides thorough experimental results as well as
detailed analysis. All of the work substantially extends the preliminary research in (Si and Callan, in: Peters (ed.) Results
of the cross-language evaluation forum-CLEF 2005, 2005).
相似文献
| Hao YuanEmail: |
5.
Precision prediction based on ranked list coherence 总被引：1，自引：0，他引：1
We introduce a statistical measure of the coherence of a list of documents called the clarity score. Starting with a document list ranked by the query-likelihood retrieval model, we demonstrate the score's relationship to query ambiguity with respect to the collection. We also show that the clarity score is correlated with the average precision of a query and lay the groundwork for useful predictions by discussing a method of setting decision thresholds automatically. We then show that passage-based clarity scores correlate with average-precision measures of ranked lists of passages, where a passage is judged relevant if it contains correct answer text, which extends the basic method to passage-based systems. Next, we introduce variants of document-based clarity scores to improve the robustness, applicability, and predictive ability of clarity scores. In particular, we introduce the ranked list clarity score that can be computed with only a ranked list of documents, and the weighted clarity score where query terms contribute more than other terms. Finally, we show an approach to predicting queries that perform poorly on query expansion that uses techniques expanding on the ideas presented earlier.
相似文献
| W. Bruce CroftEmail: |
6.
There is a wide set of evaluation metrics available to compare the quality of text clustering algorithms. In this article,
we define a few intuitive formal constraints on such metrics which shed light on which aspects of the quality of a clustering
are captured by different metric families. These formal constraints are validated in an experiment involving human assessments,
and compared with other constraints proposed in the literature. Our analysis of a wide range of metrics shows that only BCubed satisfies all formal constraints. We also extend the analysis to the problem of overlapping clustering, where items can simultaneously
belong to more than one cluster. As Bcubed cannot be directly applied to this task, we propose a modified version of Bcubed
that avoids the problems found with other metrics.
相似文献
| Felisa VerdejoEmail: |
7.
Jacob Soll 《Archival Science》2007,7(4):331-342
This article examines the archival methods developed by Colbert to train his son in state administration. Based on Colbert’s
correspondence with his son, it reveals the practices Colbert thought necessary to collect and manage information in his state
encyclopedic archive during the last half of the 17th century.
相似文献
| Jacob SollEmail: |
8.
Jun Wang Stephen Robertson Arjen P. de Vries Marcel J. T. Reinders 《Information Retrieval》2008,11(6):477-497
Collaborative filtering is concerned with making recommendations about items to users. Most formulations of the problem are
specifically designed for predicting user ratings, assuming past data of explicit user ratings is available. However, in practice
we may only have implicit evidence of user preference; and furthermore, a better view of the task is of generating a top-N
list of items that the user is most likely to like. In this regard, we argue that collaborative filtering can be directly
cast as a relevance ranking problem. We begin with the classic Probability Ranking Principle of information retrieval, proposing a probabilistic
item ranking framework. In the framework, we derive two different ranking models, showing that despite their common origin,
different factorizations reflect two distinctive ways to approach item ranking. For the model estimations, we limit our discussions
to implicit user preference data, and adopt an approximation method introduced in the classic text retrieval model (i.e. the
Okapi BM25 formula) to effectively decouple frequency counts and presence/absence counts in the preference data. Furthermore,
we extend the basic formula by proposing the Bayesian inference to estimate the probability of relevance (and non-relevance),
which largely alleviates the data sparsity problem. Apart from a theoretical contribution, our experiments on real data sets
demonstrate that the proposed methods perform significantly better than other strong baselines.
相似文献
| Marcel J. T. ReindersEmail: |
9.
Content-oriented XML retrieval approaches aim at a more focused retrieval strategy: Instead of retrieving whole documents, document components that are exhaustive to the information need while at the same time being as specific as possible should be retrieved. In this article, we show that the evaluation methods developed for standard retrieval must be modified in order to deal with the structure of XML documents. More precisely, the size and overlap of document components must be taken into account. For this purpose, we propose a new effectiveness metric based on the definition of a concept space defined upon the notions of exhaustiveness and specificity of a search result. We compare the results of this new metric by the results obtained with the official metric used in INEX, the evaluation initiative for content-oriented XML retrieval.
相似文献
| Gabriella KazaiEmail: |
10.
Massih R. Amini Anastasios Tombros Nicolas Usunier Mounia Lalmas 《Information Retrieval》2007,10(3):233-255
Documents formatted in eXtensible Markup Language (XML) are available in collections of various document types. In this paper,
we present an approach for the summarisation of XML documents. The novelty of this approach lies in that it is based on features
not only from the content of documents, but also from their logical structure. We follow a machine learning, sentence extraction-based
summarisation technique. To find which features are more effective for producing summaries, this approach views sentence extraction
as an ordering task. We evaluated our summarisation model using the INEX and SUMMAC datasets. The results demonstrate that
the inclusion of features from the logical structure of documents increases the effectiveness of the summariser, and that
the learnable system is also effective and well-suited to the task of summarisation in the context of XML documents. Our approach
is generic, and is therefore applicable, apart from entire documents, to elements of varying granularity within the XML tree.
We view these results as a step towards the intelligent summarisation of XML documents.
相似文献
| Mounia LalmasEmail: |
11.
To put an end to the large copyright trade deficit, both Chinese government agencies and publishing houses have been striving
for entering the international publication market. The article analyzes the background of the going-global strategy, and sums
up the performance of both Chinese administrations and publishers.
相似文献
| Qing Fang (Corresponding author)Email: |
12.
Fotis Lazarinis Jesús Vilares John Tait Efthimis N. Efthimiadis 《Information Retrieval》2009,12(3):230-250
With increasingly higher numbers of non-English language web searchers the problems of efficient handling of non-English Web
documents and user queries are becoming major issues for search engines. The main aim of this review paper is to make researchers
aware of the existing problems in monolingual non-English Web retrieval by providing an overview of open issues. A significant
number of papers are reviewed and the research issues investigated in these studies are categorized in order to identify the
research questions and solutions proposed in these papers. Further research is proposed at the end of each section.
相似文献
| Efthimis N. EfthimiadisEmail: |
13.
Filip Boudrez 《Archival Science》2007,7(2):179-193
This paper gives an overview of the archival issues that relate to digitally signed documents. First, by way of introduction,
the advanced digital signature is presented briefly. In the second part, a number of problems are discussed that present themselves
when a digital signature is used as a proof of authenticity and integrity for digital documents in general. In particular,
it is also being investigated whether it makes any sense for the archivist to digitally sign all electronic records under
his or her management. Problems relating to the (medium) long-term archiving of digitally signed documents are dealt with
in the third part. After an overview of the sticking points for long-term validation (“Archival issues”) a number of possible
solutions are discussed (“Solutions for long-term archiving”).
相似文献
| Filip BoudrezEmail: |
14.
Evaluation is a major driving force in advancing the state of the art in language technologies. In particular, methods for automatically assessing the quality of machine output is the preferred method for measuring progress, provided that these metrics have been validated against human judgments. Following recent developments in the automatic evaluation of machine translation and document summarization, we present a similar approach, implemented in a measure called POURPRE, an automatic technique for evaluating answers to complex questions based on n-gram co-occurrences between machine output and a human-generated answer key. Until now, the only way to assess the correctness of answers to such questions involves manual determination of whether an information “nugget” appears in a system's response. The lack of automatic methods for scoring system output is an impediment to progress in the field, which we address with this work. Experiments with the TREC 2003, TREC 2004, and TREC 2005 QA tracks indicate that rankings produced by our metric correlate highly with official rankings, and that POURPRE outperforms direct application of existing metrics.
相似文献
| Dina Demner-FushmanEmail: |
15.
Sandeep Chaufla 《Publishing Research Quarterly》2008,24(3):187-201
A review and analysis of the rules and regulations including the tax aspects of making an investment in India is presented.
The full range from Foreign Direct Investment to different forms of doing business with specific examples from the publishing
industry is explored to help understand current policies and regulations.
相似文献
| Sandeep ChauflaEmail: Email: |
16.
Xiaojun Wan 《Information Retrieval》2008,11(1):25-49
In recent years graph-ranking based algorithms have been proposed for single document summarization and generic multi-document
summarization. The algorithms make use of the “votings” or “recommendations” between sentences to evaluate the importance
of the sentences in the documents. This study aims to differentiate the cross-document and within-document relationships between
sentences for generic multi-document summarization and adapt the graph-ranking based algorithm for topic-focused summarization.
The contributions of this study are two-fold: (1) For generic multi-document summarization, we apply the graph-based ranking
algorithm based on each kind of sentence relationship and explore their relative importance for summarization performance.
(2) For topic-focused multi-document summarization, we propose to integrate the relevance of the sentences to the specified
topic into the graph-ranking based method. Each individual kind of sentence relationship is also differentiated and investigated
in the algorithm. Experimental results on DUC 2002–DUC 2005 data demonstrate the great importance of the cross-document relationships
between sentences for both generic and topic-focused multi-document summarizations. Even the approach based only on the cross-document
relationships can perform better than or at least as well as the approaches based on both kinds of relationships between sentences.
相似文献
| Xiaojun WanEmail: |
17.
Panagiotis Symeonidis Alexandros Nanopoulos Apostolos N. Papadopoulos Yannis Manolopoulos 《Information Retrieval》2008,11(1):51-75
Collaborative Filtering (CF) Systems have been studied extensively for more than a decade to confront the “information overload”
problem. Nearest-neighbor CF is based either on similarities between users or between items, to form a neighborhood of users
or items, respectively. Recent research has tried to combine the two aforementioned approaches to improve effectiveness. Traditional
clustering approaches (k-means or hierarchical clustering) has been also used to speed up the recommendation process. In this paper, we use biclustering
to disclose this duality between users and items, by grouping them in both dimensions simultaneously. We propose a novel nearest-biclusters
algorithm, which uses a new similarity measure that achieves partial matching of users’ preferences. We apply nearest-biclusters
in combination with two different types of biclustering algorithms—Bimax and xMotif—for constant and coherent biclustering,
respectively. Extensive performance evaluation results in three real-life data sets are provided, which show that the proposed
method improves substantially the performance of the CF process.
相似文献
| Yannis ManolopoulosEmail: |
18.
Arabic documents that are available only in print continue to be ubiquitous and they can be scanned and subsequently OCR’ed
to ease their retrieval. This paper explores the effect of context-based OCR correction on the effectiveness of retrieving
Arabic OCR documents using different index terms. Different OCR correction techniques based on language modeling with different
correction abilities were tested on real OCR and synthetic OCR degradation. Results show that the reduction of word error
rates needs to pass a certain limit to get a noticeable effect on retrieval. If only moderate error reduction is available,
then using short character n-gram for retrieval without error correction is not a bad strategy. Word-based correction in conjunction
with language modeling had a statistically significant impact on retrieval even for character 3-grams, which are known to
be among the best index terms for OCR degraded Arabic text. Further, using a sufficiently large language model for correction
can minimize the need for morphologically sensitive error correction.
相似文献
| Kareem DarwishEmail: |
19.
Sentence level novelty detection aims at spotting sentences with novel information from an ordered sentence list. In the task, sentences appearing later in the list with no new meanings are eliminated. For the task of novelty detection, the contributions of this paper are three-fold. First, conceptually, this paper reveals the computational nature of the task currently overlooked by the Novelty community—Novelty as a combination of partial overlap (PO) and complete overlap (CO) relations between sentences. We define partial overlap between two sentences as a sharing of common facts, while complete overlap is when one sentence covers all of the meanings of the other sentence. Second, technically, a novel approach, the selected pool method is provided which follows naturally from the PO-CO computational structure. We provide formal error analysis for selected pool and methods based on this PO-CO framework. We address the question how accurate must the PO judgments be to outperform the baseline pool method. Third, experimentally, results were presented for all the three novelty datasets currently available. Results show that the selected pool is significantly better or no worse than the current methods, an indication that the term overlap criterion for the PO judgments could be adequately accurate.
相似文献
| Shaoping MaEmail: |
20.
Beatrice S. Bartlett 《Archival Science》2007,7(4):369-390
This article describes the first half century of the Communist government’s supervision and management of the central-government
archives of the last two dynasties. Immediately with the Communist ascent to power in 1949, the new government took great
interest in assembling and protecting the country’s archival documents, readying the Ming-Qing archives for access to scholars,
and preparing for publication of selected materials. By the 1980s Beijing’s Number One Historical Archives, in charge of the
largest holding of Ming-Qing documents, had become the first Chinese authority to complete a full sorting and preliminary
catalogues for such a collection. Moreover, to facilitate searches, an attempt has recently begun to create a subject-heading
system for these and other holdings in the country. In the first half century’s final decades, foreign researchers were admitted
for the first time and tours and international exchanges began to take place.
相似文献
| Beatrice S. BartlettEmail: |