NDLI: Extending language modeling techniques to models of search and browsing activity in a digital library

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On iterative intelligent medical search

Towards breaking the quality curse.: a web-querying approach to web people search.

Score standardization for inter-collection comparison of retrieval systems

Attack resistant collaborative filtering

A boosting algorithm for learning bipartite ranking functions with partially labeled data

Asymmetric distance estimation with sketches for similarity search in high-dimensional spaces

User adaptation: good results from poor systems

The opposite of smoothing: a language model approach to ranking query-specific document clusters

A study of learning a merge model for multilingual information retrieval

A study of methods for negative relevance feedback

Learning to rank with partially-labeled data

Query-sensitive mutual reinforcement chain and its application in query-oriented multi-document summarization

Algorithmic mediation for collaborative exploratory search

A user browsing model to predict search engine click data from past observations.

Learning to reduce the semantic gap in web image retrieval and annotation

A few examples go a long way: constructing query models from elaborate query formulations

Affective feedback: an investigation into the role of emotions in the information seeking process

Discriminative probabilistic models for passage based retrieval

Separate and inequal: preserving heterogeneity in topical authority flows

Finding question-answer pairs from online forums

Discovering key concepts in verbose queries

Real-time automatic tag recommendation

Spectral geometry for simultaneously clustering and ranking query search results

SpotSigs: robust and efficient near duplicate detection in large web collections

A new rank correlation coefficient for information retrieval

Deep classification in large-scale text hierarchies

Evaluation over thousands of queries

Relevance judgments between TREC and Non-TREC assessors

Personal vs non-personal blogs: initial classification experiments

AdImage: video advertising by image matching and ad scheduling optimization

A method for transferring retrieval scores between collections with non-overlapping vocabularies

XML-aided phrase indexing for hypertext documents

Minexml: bridging unstructured query with structured resources via mediated query

Exploiting XML structure to improve information retrieval in peer-to-peer systems

Delighting Chinese users: the Google China experience

Effective and efficient user interaction for long queries

An unsupervised framework for extracting and normalizing product attributes from multiple web sites

The good and the bad system: does the test collection predict users' effectiveness?

EigenRank: a ranking-oriented approach to collaborative filtering

Directly optimizing evaluation measures in learning to rank

ResIn: a combination of results caching and index pruning for high-performance web search engines

Exploring folksonomy for personalized search

Enhancing text clustering by leveraging Wikipedia semantics

Bilingual topic aspect classification with a few training examples

A bayesian logistic regression model for active relevance feedback

Learning to rank with SoftRank and Gaussian processes

Comments-oriented document summarization: understanding documents with readers' feedback

Exploiting correlated keywords to improve approximate information filtering

Learning query intent from regularized click graphs

A lattice-based approach to query-by-example spoken document retrieval

A unified and discriminative model for query refinement

Optimizing relevance and revenue in ad search: a query substitution approach

A new probabilistic retrieval model based on the dirichlet compound multinomial distribution

BrowseRank: letting web users vote for page importance

Retrieval models for question and answer archives

Ambiguous queries: test collections need more sense

Efficient top-k querying over social-tagging networks

A rank-aggregation approach to searching for optimal query-specific clusters

Local text reuse detection

Learning from labeled features using generalized expectation criteria

Topic-bridged PLSA for cross-domain text classification

Novelty and diversity in information retrieval evaluation

Evaluation measures for preference judgments

Exploiting subjectivity analysis in blogs to improve political leaning categorization

Bag-of-visual-words expansion using visual relatedness for video indexing

Improving relevance feedback in language modeling with score regularization

Proximity-aware scoring for XML retrieval

Clustering search results for mobile terminals

Affective feedback: an investigation into the role of emotions in the information seeking process

Guilt by association as a search principle

How do users find things with PubMed?: towards automatic utility evaluation with user simulations

Enhancing web search by promoting multiple search engine use

Retrieval sensitivity under training using different measures

Personalized active learning for collaborative filtering

Query dependent ranking using K-nearest neighbor

Reorganizing compressed text

To personalize or not to personalize: modeling queries with variation in user intent

Knowledge transformation from word space to document space

Crosslingual location search

A cluster-based resampling method for pseudo-relevance feedback

Learning to rank at query-time using association rules

Multi-document summarization using cluster-based link analysis

Retrieval and feedback models for blog feed search

Query expansion using gaze-based feedback on the subdocument level

A generation model to unify topic relevance and lexicon-based sentiment for opinion retrieval

TF-IDF uncovered: a study of theories and probabilities

Exploring traversal strategy for web forum crawling

Predicting information seeker satisfaction in community question answering

Automatically identifying localizable queries

Social tag prediction

A comparative evaluation of different link types on enhancing document clustering

TSCAN: a novel method for topic summarization and content anatomy

A simple and efficient sampling method for estimating AP and NDCG

trNon-greedy active learning for text categorization using convex ansductive experimental design

Relevance assessment: are judges exchangeable and does it matter

Exploring evaluation metrics: GMAP versus MAP

Ranking opinionated blog posts using OpinionFinder

A word shape coding method for camera-based document images

Theoretical bounds on and empirical robustness of score regularization to different similarity measures

Locating relevant text within XML documents

Refining search results with facet landscapes

Exploring and measuring dependency trees for informationretrieval

Selecting good expansion terms for pseudo-relevance feedback

Learning to rank with ties

Multi-document summarization via sentence-level semantic analysis and symmetric matrix factorization

A general optimization framework for smoothing language models on graph structures

Classifiers without borders: incorporating fielded text from neighboring web pages

Intuition-supporting visualization of user's performance based on explicit negative higher-order relevance

A new interpretation of average precision

Searching blogs and news: a study on popular queries

Term clouds as surrogates for user generated speech

A study of query length

A flexible extension of XPath to improve XML querying

Ice-tea: an interactive cross-language search engine with translation enhancement

The search for expertise: to the documents and beyond

Comparing metrics across TREC and NTCIR:: the robustness to pool depth bias

Aggregated click-through data in a homogeneous user community

A faceted interface for multimedia search

Don't have a stemmer?: be un+concern+ed

Combining document- and paragraph-based entity ranking

Cross-lingual search over 22 european languages

Task detection for activity-based desktop search

Relevance thresholds in system evaluations

To tag or not to tag -: harvesting adjacent metadata in large-scale tagging systems

WISA: a novel web image semantic analysis system

Parsimonious concept modeling

Re-ranking search results using document-passage graphs

Social recommendations at work

Using a mediated query approach for matching unstructured query with structured resources

Precision-at-ten considered redundant

Exploring question subjectivity prediction in community QA

One-button search extracts wider interests: an empirical study with video bookmarking search

Parsimonious relevance models

Utilizing phrase based semantic information for term dependency

Bilkent news portal: a personalizable system with new event detection and tracking capabilities

Understanding system implementation and user behavior in a collaborative information seeking environment

Structuring collections with Scatter/Gather extensions

On the evolution of the yahoo! answers QA community

Product retrieval for grocery stores

Author-topic evolution analysis using three-way non-negative Paratucker

Inferring the most important types of a query: a semantic approach

Geographic IR and visualization in time and space

Biomedical cross-language information retrieval

Text collections for FIRE

Detecting synonyms in social tagging systems to improve content retrieval

A reranking model for genomics aspect search

Exploiting proximity feature in bigram language model for information retrieval

On multiword entity ranking in peer-to-peer search

Fine-grained relevance feedback for XML retrieval

Towards a combined model for search and navigation of annotated documents

A longitudinal study of real-time search assistance adoption

SOPING: a Chinese customer review mining system

Improving biomedical document retrieval using domain knowledge

Measuring concept relatedness using language models

Site-based dynamic pruning for query processing in search engines

Dynamic visualization of music classification systems

Context and linking in retrieval from personal digital archives

TopicRank: bringing insight to users

Combining learn-based and lexicon-based techniques for sentiment detection without using labeled examples

Kleio: a knowledge-enriched information retrieval system for biology

Query-drift prevention for robust query expansion

Exploiting MDS Projections for Cross-language IR

From concepts to implementation and visualization: tools from a team-based approach to ir

Extending language modeling techniques to models of search and browsing activity in a digital library

Talking the talk vs. walking the walk: salience of information needs in querying vs. browsing

Semi-supervised spam filtering: does it work?

Enhancing keyword-based botanical information retrieval with information extraction

Adaptive label-driven scaling for latent semantic indexing

Local approximation of PageRank and reverse PageRank

Exploring mouse movements for inferring query intent

Limits of opinion-finding baseline systems

How medical expertise influences web search interaction

Fixed-threshold SMO for Joint Constraint Learning Algorithm of Structural SVM

Improving text classification accuracy using topic modeling over an additional corpus

Emulating query-biased summaries using document titles

Web query translation via web log mining

Generating diverse katakana variants based on phonemic mapping

Posterior probabilistic clustering using NMF

An algorithm for text categorization

Hierarchical naive bayes models for representing user profiles

Analyzing web text association to disambiguate abbreviation in queries

Exploiting sequential dependencies for expert finding

On document splitting in passage detection

Hypergraph partitioning for document clustering: a unified clique perspective

A topical PageRank based algorithm for recommender systems

Bloggers as experts: feed distillation using expert retrieval models

Modeling expert finding as an absorbing random walk

Learning with support vector machines for query-by-multiple-examples

Pagerank based clustering of hypertext document collections

The impact of history length on personalized search

Search effectiveness with a breadth-first crawl

A scalable assistant librarian: hierarchical subject classification of books

Question classification with semantic tree kernel

An alignment-based pattern representation model for information extraction

User preference choices for complex question answering

Guide focused crawler efficiently and effectively using on-line topical importance estimation

Information retrieval on bug locations by learning co-located bug report clusters

Generalising multiple capture-recapture to non-uniform sample sizes

Relational distance-based collaborative filtering

Towards personalized distributed information retrieval

Web page retrieval in ubiquitous sensor environments

Summarization of compressed text images: an experience on Indic script documents

Predicting when browsing context is relevant to search

Task-aware search personalization

Automatic document prior feature selection for web retrieval

Using parsimonious language models on web data

Query preprocessing: improving web search through a Vietnamese word tokenization approach

Extending language modeling techniques to models of search and browsing activity in a digital library

Content Provider	ACM Digital Library
Author	Murray, G. Craig
Abstract	Users searching for information in a digital library or on the WWW can be modeled as individuals moving through a semantic space by issuing queries and clicking on hyperlinks. As they go, they emit a stream of interaction data. Most of it is linguistic data. Lots of it is captured in logs. Some of it is used to guess what the user is searching for. But to most information retrieval systems, each user interaction is a stateless point in this space. There is a timeline connecting each of these points, but systems seldom make use of this as sequence data, in part because there is no clear way to systematically characterize the meaningful relations within a sequence of user activity. It is a problem of pragmatics as much as it is of semantics--the fact that a user clicked on a particular link, or added a particular term to their query, has meaning primarily in relation to the preceding actions. A remaining challenge in IR is to extract features of the user interaction data that will give meaning to those relations. Meanwhile, from the user's perspective each of these points in time and semantic space are just part of a path of exploration. To the user, the exact terms in a query, or the specific words surrounding a hypertext link, may be less important than the trajectory those terms establish in relation to the user's path. Identifying the meaningful relations between queries and page views within a sequence of activity increases our understanding of users and their information needs. Formally, we can model query and browsing behaviors as surface forms of a hidden process. What is missing is a layer of abstraction for mapping sequences of interaction in a way that is both descriptive of users' needs and useful to automation. The work I describe is an effort to identify features of data in logs of query and browsing activity that are highly predictive of certain types of behavior. Sequences of interaction data from individual users are modeled as sequences of expression. Statistical modeling techniques that are effective for modeling sequences in natural language processing and bioinformatics are examined for their ability to model sequences of interaction between an information searcher and an information retrieval system. Queries and click-throughs in this stream of interaction can be tagged with features such as semantic coordinates, timing, frequency of use, type of action, etc. By analyzing large collections of interaction sequences it is possible to identify frequent patterns of user behavior. From these patterns we can make predictions about future interactions. For example, certain patterns of link following in a digital library are highly predictive of users' next steps while other patterns are not. General models of user interaction are useful for design and evaluation of search interfaces. Individual models of user interaction are useful for personalized search and customized content. Yet very little research has been done to investigate which features are optimal for modeling user queries and browsing as interaction sequences. An important first step is to identify informative features and the relationships between features. I propose to construct models of user behavior based on user data in logs of query and browsing activity and to identify features that are highly predictive of certain types of user behaviors. I examine activity within search sessions on a digital library as a microcosm of larger systems. I expect to find features that are useful in predictive models of user behavior both at an individual and aggregate level. Where possible, I hope to identify meaningful relationships between those features. The work has implications beyond the scope of digital libraries, to larger systems and broader search domains.
Starting Page	900
Ending Page	900
Page Count	1
File Format	PDF
ISBN	9781605581644
DOI	10.1145/1390334.1390575
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2008-07-20
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Search behavior Sequence data Web logs Predictive models Query modeling
Content Type	Text
Resource Type	Article

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