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1.
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: |
2.
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: |
3.
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: |
4.
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: |
5.
On rank-based effectiveness measures and optimization 总被引：1，自引：0，他引：1
Many current retrieval models and scoring functions contain free parameters which need to be set—ideally, optimized. The process
of optimization normally involves some training corpus of the usual document-query-relevance judgement type, and some choice
of measure that is to be optimized. The paper proposes a way to think about the process of exploring the space of parameter
values, and how moving around in this space might be expected to affect different measures. One result, concerning local optima,
is demonstrated for a range of rank-based evaluation measures.
相似文献
| Hugo ZaragozaEmail: |
6.
Norbert Fuhr 《Information Retrieval》2008,11(3):251-265
The classical Probability Ranking Principle (PRP) forms the theoretical basis for probabilistic Information Retrieval (IR)
models, which are dominating IR theory since about 20 years. However, the assumptions underlying the PRP often do not hold,
and its view is too narrow for interactive information retrieval (IIR). In this article, a new theoretical framework for interactive
retrieval is proposed: The basic idea is that during IIR, a user moves between situations. In each situation, the system presents
to the user a list of choices, about which s/he has to decide, and the first positive decision moves the user to a new situation.
Each choice is associated with a number of cost and probability parameters. Based on these parameters, an optimum ordering
of the choices can the derived—the PRP for IIR. The relationship of this rule to the classical PRP is described, and issues
of further research are pointed out.
相似文献
| Norbert FuhrEmail: |
7.
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: |
8.
Result merging methods in distributed information retrieval with overlapping databases 总被引：5，自引：0，他引：5
In distributed information retrieval systems, document overlaps occur frequently among different component databases. This
paper presents an experimental investigation and evaluation of a group of result merging methods including the shadow document
method and the multi-evidence method in the environment of overlapping databases. We assume, with the exception of resultant
document lists (either with rankings or scores), no extra information about retrieval servers and text databases is available,
which is the usual case for many applications on the Internet and the Web.
The experimental results show that the shadow document method and the multi-evidence method are the two best methods when
overlap is high, while Round-robin is the best for low overlap. The experiments also show that [0,1] linear normalization
is a better option than linear regression normalization for result merging in a heterogeneous environment.
相似文献
| Sally McCleanEmail: |
9.
A comparison of analyses of the Scottish publishing industry carried out in 1992, 2002 and 2007 underscores the fragility
of the sector within a small country within the English-language community. A number of indices reveal either stability or
stagnation and the picture emerges of the remarkable tenacity of publishing in Scotland. Although there is already a significant
and vital element of state support for publishing in Scotland, further intervention will be necessary to ensure fulfilment
of its potential.
相似文献
| Alistair McCleeryEmail: |
10.
Modeling context through domain ontologies 总被引：1，自引：0，他引：1
Nathalie Hernandez Josiane Mothe Claude Chrisment Daniel Egret 《Information Retrieval》2007,10(2):143-172
Traditional information retrieval systems aim at satisfying most users for most of their searches, leaving aside the context
in which the search takes place. We propose to model two main aspects of context: The themes of the user's information need
and the specific data the user is looking for to achieve the task that has motivated his search. Both aspects are modeled
by means of ontologies. Documents are semantically indexed according to the context representation and the user accesses information
by browsing the ontologies. The model has been applied to a case study that has shown the added value of such a semantic representation
of context.
相似文献
| Daniel EgretEmail: |
11.
Due to the heavy use of gene synonyms in biomedical text, people have tried many query expansion techniques using synonyms
in order to improve performance in biomedical information retrieval. However, mixed results have been reported. The main challenge
is that it is not trivial to assign appropriate weights to the added gene synonyms in the expanded query; under-weighting
of synonyms would not bring much benefit, while overweighting some unreliable synonyms can hurt performance significantly.
So far, there has been no systematic evaluation of various synonym query expansion strategies for biomedical text. In this
work, we propose two different strategies to extend a standard language modeling approach for gene synonym query expansion
and conduct a systematic evaluation of these methods on all the available TREC biomedical text collections for ad hoc document
retrieval. Our experiment results show that synonym expansion can significantly improve the retrieval accuracy. However, different
query types require different synonym expansion methods, and appropriate weighting of gene names and synonym terms is critical
for improving performance.
相似文献
| Chengxiang ZhaiEmail: |
12.
Andrew MacFarlane 《Information Retrieval》2009,12(2):162-178
Understanding of mathematics is needed to underpin the process of search, either explicitly with Exact Match (Boolean logic,
adjacency) or implicitly with Best match natural language search. In this paper we outline some pedagogical challenges in
teaching mathematics for information retrieval (IR) to postgraduate information science students. The aim is to take these
challenges either found by experience or in the literature, to identify both theoretical and practical ideas in order to improve
the delivery of the material and positively affect the learning of the target audience by using a tutorial style of teaching.
Results show that there is evidence to support the notion that a more pro-active style of teaching using tutorials yield benefits
both in terms of assessment results and student satisfaction.
相似文献
| Andrew MacFarlaneEmail: |
13.
Oren Kurland 《Information Retrieval》2009,12(4):437-460
To obtain high precision at top ranks by a search performed in response to a query, researchers have proposed a cluster-based
re-ranking paradigm: clustering an initial list of documents that are the most highly ranked by some initial search, and using
information induced from these (often called) query-specific clusters for re-ranking the list. However, results concerning the effectiveness of various automatic cluster-based re-ranking methods have been inconclusive. We show that using query-specific clusters for automatic re-ranking
of top-retrieved documents is effective with several methods in which clusters play different roles, among which is the smoothing of document language models. We do so by adapting previously-proposed cluster-based retrieval approaches, which are based on (static) query-independent
clusters for ranking all documents in a corpus, to the re-ranking setting wherein clusters are query-specific. The best performing
method that we develop outperforms both the initial document-based ranking and some previously proposed cluster-based re-ranking
approaches; furthermore, this algorithm consistently outperforms a state-of-the-art pseudo-feedback-based approach. In further
exploration we study the performance of cluster-based smoothing methods for re-ranking with various (soft and hard) clustering
algorithms, and demonstrate the importance of clusters in providing context from the initial list through a comparison to
using single documents to this end.
相似文献
| Oren KurlandEmail: |
14.
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: |
15.
The complexity and diversity of government regulations make understanding and retrieval of regulations a non-trivial task. One of the issues is the existence of multiple sources of regulations and interpretive guides with differences in format, terminology and context. This paper describes a comparative analysis scheme developed to help retrieval of related provisions from different regulatory documents. Specifically, the goal is to identify the most strongly related provisions between regulations. The relatedness analysis makes use of not only traditional term match but also a combination of feature matches, and not only content comparison but also structural analysis.Regulations are first compared based on conceptual information as well as domain knowledge through feature matching. Regulations also possess specific organizational structures, such as a tree hierarchy of provisions and heavy referencing between provisions. These structures represent useful information in locating related provisions, and are therefore exploited in the comparison of regulations for completeness. System performance is evaluated by comparing a similarity ranking produced by users with the machine-predicted ranking. Ranking produced by the relatedness analysis system shows a reduction in error compared to that of Latent Semantic Indexing. Various pairs of regulations are compared and the results are analyzed along with observations based on different feature usages. An example of an e-rulemaking scenario is shown to demonstrate capabilities and limitations of the prototype relatedness analysis system.
相似文献
| Gio WiederholdEmail: |
16.
Document length is widely recognized as an important factor for adjusting retrieval systems. Many models tend to favor the
retrieval of either short or long documents and, thus, a length-based correction needs to be applied for avoiding any length
bias. In Language Modeling for Information Retrieval, smoothing methods are applied to move probability mass from document
terms to unseen words, which is often dependant upon document length. In this article, we perform an in-depth study of this
behavior, characterized by the document length retrieval trends, of three popular smoothing methods across a number of factors,
and its impact on the length of documents retrieved and retrieval performance. First, we theoretically analyze the Jelinek–Mercer,
Dirichlet prior and two-stage smoothing strategies and, then, conduct an empirical analysis. In our analysis we show how Dirichlet
prior smoothing caters for document length more appropriately than Jelinek–Mercer smoothing which leads to its superior retrieval
performance. In a follow up analysis, we posit that length-based priors can be used to offset any bias in the length retrieval
trends stemming from the retrieval formula derived by the smoothing technique. We show that the performance of Jelinek–Mercer
smoothing can be significantly improved by using such a prior, which provides a natural and simple alternative to decouple
the query and document modeling roles of smoothing. With the analysis of retrieval behavior conducted in this article, it
is possible to understand why the Dirichlet Prior smoothing performs better than the Jelinek–Mercer, and why the performance
of the Jelinek–Mercer method is improved by including a length-based prior.
相似文献
| Leif AzzopardiEmail: |
17.
Andy Weissberg 《Publishing Research Quarterly》2008,24(4):255-260
This article analyzes current industry practices toward the identification of digital book content. It highlights key technology
trends, workflow considerations and supply chain behaviors, and examines the implications of these trends and behaviors on
the production, discoverability, purchasing and consumption of digital book products.
相似文献
| Andy WeissbergEmail: |
18.
A summary overview of the children’s and young adult publishing industry in China with a focus on the size of the market,
ten major publishing houses, copyright and trends. Special emphasis has been placed on specific transaction for the sale of
translation rights from German language publishers to China and minimal activities of German rights sold to Chinese publishers.
相似文献
| Jing BartzEmail: |
19.
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: |
20.
Intelligent use of the many diverse forms of data available on the Internet requires new tools for managing and manipulating
heterogeneous forms of information. This paper uses WHIRL, an extension of relational databases that can manipulate textual
data using statistical similarity measures developed by the information retrieval community. We show that although WHIRL is
designed for more general similarity-based reasoning tasks, it is competitive with mature systems designed explicitly for
inductive classification. In particular, WHIRL is well suited for combining different sources of knowledge in the classification
process. We show on a diverse set of tasks that the use of appropriate sets of unlabeled background knowledge often decreases
error rates, particularly if the number of examples or the size of the strings in the training set is small. This is especially
useful when labeling text is a labor-intensive job and when there is a large amount of information available about a particular
problem on the World Wide Web.
相似文献
| Haym HirshEmail: |