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  1. Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval (SIGIR '06)
  2. Quantum haystacks
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Learning user interaction models for predicting web search result preferences
Contextual search and name disambiguation in email using graphs
Spoken document retrieval from call-center conversations
AggregateRank: bringing order to web sites
The role of knowledge in conceptual retrieval: a study in the domain of clinical medicine
On-line spam filter fusion
Using web-graph distance for relevance feedback in web search
Context-sensitive semantic smoothing for the language modeling approach to genomic IR
A study of statistical models for query translation: finding a good unit of translation
Probabilistic model for definitional question answering
Latent semantic analysis for multiple-type interrelated data objects
Evaluation in (XML) information retrieval: expected precision-recall with user modelling (EPRUM)
Finding near-duplicate web pages: a large-scale evaluation of algorithms
Capturing collection size for distributed non-cooperative retrieval
Load balancing for term-distributed parallel retrieval
Mining dependency relations for query expansion in passage retrieval
Document clustering with prior knowledge
Less is more: probabilistic models for retrieving fewer relevant documents
Elicitation of term relevance feedback: an investigation of term source and context
Large scale semi-supervised linear SVMs
Unifying user-based and item-based collaborative filtering approaches by similarity fusion
Evaluating evaluation metrics based on the bootstrap
Learning to advertise
A compositional context sensitive multi-document summarizer: exploring the factors that influence summarization
Clustering of search results using temporal attributes
The TIJAH XML information retrieval system
Quantum haystacks
User performance versus precision measures for simple search tasks
Thread detection in dynamic text message streams
Towards efficient automated singer identification in large music databases
Respect my authority!: HITS without hyperlinks, utilizing cluster-based language models
A parallel derivation of probabilistic information retrieval models
Building bridges for web query classification
Improving the estimation of relevance models using large external corpora
LDA-based document models for ad-hoc retrieval
Combining bidirectional translation and synonymy for cross-language information retrieval
Answering complex questions with random walk models
Identifying comparative sentences in text documents
Minimal test collections for retrieval evaluation
Structure-driven crawler generation by example
Probabilistic latent query analysis for combining multiple retrieval sources
Hybrid index maintenance for growing text collections
What makes a query difficult?
Text clustering with extended user feedback
High accuracy retrieval with multiple nested ranker
Find-similar: similarity browsing as a search tool
Graph-based text classification: learn from your neighbors
Personalized recommendation driven by information flow
Statistical precision of information retrieval evaluation
Getting work done on the web: supporting transactional queries
Information graphics: an untapped resource for digital libraries
A complex document information processing prototype
A location annotation system for personal photos
Social networks, incentives, and search
Improving web search ranking by incorporating user behavior information
Formal models for expert finding in enterprise corpora
Music structure based vector space retrieval
Topical link analysis for web search
Semantic term matching in axiomatic approaches to information retrieval
ProbFuse: a probabilistic approach to data fusion
Regularized estimation of mixture models for robust pseudo-relevance feedback
Adapting ranking SVM to document retrieval
A framework to predict the quality of answers with non-textual features
Tackling concept drift by temporal inductive transfer
Dynamic test collections: measuring search effectiveness on the live web
Building implicit links from content for forum search
User modeling for full-text federated search in peer-to-peer networks
Type less, find more: fast autocompletion search with a succinct index
On ranking the effectiveness of searches
Near-duplicate detection by instance-level constrained clustering
Semantic search via XML fragments: a high-precision approach to IR
Exploring the limits of single-iteration clarification dialogs
Constructing informative prior distributions from domain knowledge in text classification
Analysis of a low-dimensional linear model under recommendation attacks
A statistical method for system evaluation using incomplete judgments
You are what you say: privacy risks of public mentions
News to go: hierarchical text summarization for mobile devices
Inferring document relevance via average precision
Appraisal navigator
Information retrieval at Boeing: plans and successes
Generalizing PageRank: damping functions for link-based ranking algorithms
Distributed query sampling: a quality-conscious approach
Pruned query evaluation using pre-computed impacts
Automatic construction of known-item finding test beds
A platform for Okapi-based contextual information retrieval
Adaptive query-based sampling for distributed IR
Project contexts to situate personal information
PENG: integrated search of distributed news archives
Cheshire3: retrieving from tera-scale grid-based digital libraries
Examining assessor attributes at HARD 2005
DeWild: a tool for searching the web using wild cards
User expectations from XML element retrieval
Searching for expertise using the terrier platform
Theoretical benchmarks of XML retrieval
DiLight: an ontology-based information access system for e-learning environments
Question classification with log-linear models
Supporting semantic visual feature browsing in contentbased video retrieval
Community-based snippet-indexes for pseudo-anonymous personalization in web search
MathFind: a math-aware search engine
Bias and the limits of pooling
Term proximity scoring for ad-hoc retrieval on very large text collections
An exploratory web log study of multitasking
Tensor space model for document analysis
First large-scale information retrieval experiments on turkish texts
Learning a ranking from pairwise preferences
Automated performance assessment in interactive QA
Stylistic text segmentation
On hierarchical web catalog integration with conceptual relationships in thesaurus
Rpref: a generalization of Bpref towards graded relevance judgments
A new web page summarization method
NMF and PLSI: equivalence and a hybrid algorithm
Using historical data to enhance rank aggregation
Enterprise search behaviour of software engineers
Evaluating sources of query expansion terms
Comparing two blind relevance feedback techniques
Information retrieval with commonsense knowledge
Refining hierarchical taxonomy structure via semi-supervised learning
Quantative analysis of the impact of judging inconsistency on the performance of relevance feedback
Swordfish: an unsupervised Ngram based approach to morphological analysis
Authorship attribution with thousands of candidate authors
Simple questions to improve pseudo-relevance feedback results
Is XML retrieval meaningful to users?: searcher preferences for full documents vs. elements
Building a test collection for complex document information processing
Enhancing topic tracking with temporal information
A comparative study of the effect of search feature design on user experience in digital libraries (DLs)
Representing clusters for retrieval
One-sided measures for evaluating ranked retrieval effectiveness with spontaneous conversational speech
Combining fields in known-item email search
Improving QA retrieval using document priors
Content-based video retrieval: does video's semantic visual feature matter?
Action modeling: language models that predict query behavior
A method of rating the credibility of news documents on the web
An analysis of the coupling between training set and neighborhood sizes for the kNN classifier
Fact-focused novelty detection: a feasibility study
Unity: relevance feedback using user query logs
Improving personalized web search using result diversification
Using small XML elements to support relevance
Give me just one highly relevant document: P-measure
Feature diversity in cluster ensembles for robust document clustering
Lightening the load of document smoothing for better language modeling retrieval
The effect of OCR errors on stylistic text classification
History repeats itself: repeat queries in Yahoo's logs
Early precision measures: implications from the downside of blind feedback
An experimental study on automatically labeling hierarchical clusters using statistical features
Strict and vague interpretation of XML-retrieval queries
Why structural hints in queries do not help XML-retrieval
Searching the web using composed pages
A study of real-time query expansion effectiveness
A graph-based framework for relation propagation and its application to multi-label learning
Measuring similarity of semi-structured documents with context weights
Incorporating query difference for learning retrieval functions in information retrieval
Concept-based biomedical text retrieval

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Quantum haystacks

Content Provider ACM Digital Library
Author van Rijsbergen, C. J. 'Keith'
Abstract This acceptance talk is a curious mixture of personal history and developing ideas in the context of the growing field of IR covering several decades. I want to concentrate on models and theories, interpreted loosely, and try and give an insight into where I have got to in my thinking, where the ideas came from, and where I believe we are going.In the last few years I have been working on the development of what might be coined as a design language for IR. It takes its inspiration from Quantum Mechanics, but by analogy only. The mathematical objects represent documents; these objects might be vectors (or density operators) in an n-dimensional vector space (usually a Hilbert space). A request for information, or a query, is taken as an observable and is represented as a linear operator on the space. Linear operators can be expressed as matrices. Such an operator, Hermitian, has a set of eigenvectors forming a basis for the space; which we interpret as a point of view or perspective from which to understand the space. Thus any document-vector can be located with respect to the basis, and we can calculate an inner product between such a vector and any basis vector, which may be interpreted as a probability of relevance. The probability of observing any given eigenvector is now given by the square of that inner product assuming all vectors are normalised. Hence we connect the probability of observation to the geometry of the space. Furthermore, the subspaces of the space make up a lattice structure which is equivalent to a logic. This makes up the entire mathematical structure, and the language for handling this structure is linear algebra: vectors, matrices, projections, inner-products, neatly captured by the Dirac notation used in quantum mechanics. Our probability is slightly different from classical probability, the same for logic; we end up with quantum logic and quantum probability.A commitment to this kind of mathematical structure, with which to model objects and processes in IR, depends on two critical assumptions.The distances in the space between objects are a source of important relationships with respect to relevance and aboutness.The observation of a property such as relevance or aboutness is user dependent in the sense that a potential interaction is specified by a user through an operator which when measured achieves outcomes with a probability determined by the geometry of the space.The geometry of this mathematical structure and the probability defined on it are closely connected by the following theorem due to Gleason (1957). One may summarise this theorem by saying that the probability of a subspace is given by a simple algorithm derived from a projection onto the subspace and a special kind of operator, namely a statistical operator, or density matrix. And conversely, that given a probability measure on the subspaces then we can encode that measure uniquely through such an algorithm. This is a very powerful theorem and its consequences remain to be explored.So how did I get to this point and form of abstraction? Most of my research work can be divided into contributions to the following areas:ClusteringEvaluationProbabilistic ModelsLogic ModelsGeometry.In all these areas I have attempted to search for underlying mathematical structures that would lead to computations. These topics have in common that they depend on the construction of measures on a space which in some sense determines the usefulness or effectiveness of the structure. For clustering one considers mapping from metric spaces to ultrametic spaces and measure the closeness of fit. In the case of evaluation, one starts with a relational conjoint structure and imposes some constraints given by what is to be measured, one then constructs a numerical representation of this structure leading to such measures as F (or E). For probabilistic models the main difficulty is concerned with deciding on an appropriate event space on which to define the 'right' probability measures. For me the most significant example in this context was the attempt to construct a Logical Uncertainty Principle which formulated a measure of uncertainty on incomplete logical constructs. This attempt left unspecified the exact form of the measure. In the Geometry of IR I finally managed to formulate that measure as a projection-valued measure.This way of thinking did not appear out of nowhere. It was heavily influenced by the work of Fairthorne(1961) whose work on Brouwerian Logic (an Intuitionistic Logic) was picked up by Salton in his early book on IR. At an earlier stage MacKay (1950) wrote a paper that opened with, 'This paper relates to the borderline linking experimental and theoretical physics with mathematical logic, and covers at several points ground which is common to the theory of communication.' He goes on to define an 'information-operator' which is very similar in scope and intent to the Hermitian operator above. Maron, who collaborated with MacKay, stated in his 1965 paper, 'Therefore, it can be argued that index descriptions should not be viewed as properties of documents: They function to relate documents and users.' One can see that the development of these early ideas was continued to the construction of the Geometry of IR.What does it leave to be done? An attempt should be made to use this design language to build an IR system. On the theoretical front it is worth considering whether it would be better to start with a transition probability space rather than a Hilbert space as Von Neumann did in 1937 (translated in 1981). The assumption that closed linear subspaces will be the elements of our logic can be challenged, as perhaps a construction with different elements is possible. It is not obvious what the best form of conditional probability might be in these spaces. Agreeing on a form of conditionalisation is intimately tied up with how to model contextuality. There is some evidence to suggest that contextuality plays a role in modelling the conjuncton of concepts (Widdows, 2004). Such contexts have been modelled in quantum theory almost from the beginning, for example, Gleason's theorem precludes noncontextual hidden variable theories.
Starting Page 1
Ending Page 2
Page Count 2
File Format PDF
ISBN 1595933697
DOI 10.1145/1148170.1148171
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2006-08-06
Publisher Place New York
Access Restriction Subscribed
Content Type Text
Resource Type Article
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