Search Results for author: Alistair Moffat

Found 17 papers, 6 papers with code

Categorical, Ratio, and Professorial Data: The Case for Reciprocal Rank

no code implementations20 Dec 2023 Alistair Moffat

Search engine results pages are usually abstracted as binary relevance vectors and hence are categorical data, meaning that only a limited set of operations is permitted, most notably tabulation of occurrence frequencies, with determination of medians and averages not possible.


Stochastic Directly-Follows Process Discovery Using Grammatical Inference

no code implementations9 Dec 2023 Hanan Alkhammash, Artem Polyvyanyy, Alistair Moffat

We propose a new approach for discovering sound Directly-Follows Graphs that is grounded in grammatical inference over the input traces.

How Much Freedom Does An Effectiveness Metric Really Have?

1 code implementation18 Sep 2023 Alistair Moffat, Joel Mackenzie

It is tempting to assume that because effectiveness metrics have free choice to assign scores to search engine result pages (SERPs) there must thus be a similar degree of freedom as to the relative order that SERP pairs can be put into.

Efficient Immediate-Access Dynamic Indexing

no code implementations11 Nov 2022 Alistair Moffat, Joel Mackenzie

In a dynamic retrieval system, documents must be ingested as they arrive, and be immediately findable by queries.


Batch Evaluation Metrics in Information Retrieval: Measures, Scales, and Meaning

no code implementations7 Jul 2022 Alistair Moffat

A sequence of recent papers has considered the role of measurement scales in information retrieval (IR) experimentation, and presented the argument that (only) uniform-step interval scales should be used, and hence that well-known metrics such as reciprocal rank, expected reciprocal rank, normalized discounted cumulative gain, and average precision, should be either discarded as measurement tools, or adapted so that their metric values lie at uniformly-spaced points on the number line.

Information Retrieval Retrieval

A Sensitivity Analysis of the MSMARCO Passage Collection

no code implementations6 Dec 2021 Joel Mackenzie, Matthias Petri, Alistair Moffat

The recent MSMARCO passage retrieval collection has allowed researchers to develop highly tuned retrieval systems.

Passage Retrieval Retrieval

Bootstrapping Generalization of Process Models Discovered From Event Data

1 code implementation8 Jul 2021 Artem Polyvyanyy, Alistair Moffat, Luciano García-Bañuelos

Generalization is also perhaps the least understood of those criteria, with that lack primarily a consequence of it measuring properties over the entire future behavior of the system when the only available sample of behavior is that provided by the log.

Anytime Ranking on Document-Ordered Indexes

1 code implementation18 Apr 2021 Joel Mackenzie, Matthias Petri, Alistair Moffat

Inverted indexes continue to be a mainstay of text search engines, allowing efficient querying of large document collections.


1 code implementation9 Nov 2020 Rodger Benham, Alistair Moffat, J. Shane Culpepper

Search engine users rarely express an information need using the same query, and small differences in queries can lead to very different result sets.

Entropia: A Family of Entropy-Based Conformance Checking Measures for Process Mining

no code implementations21 Aug 2020 Artem Polyvyanyy, Hanan Alkhammash, Claudio Di Ciccio, Luciano García-Bañuelos, Anna Kalenkova, Sander J. J. Leemans, Jan Mendling, Alistair Moffat, Matthias Weidlich

This paper presents a command-line tool, called Entropia, that implements a family of conformance checking measures for process mining founded on the notion of entropy from information theory.

An Entropic Relevance Measure for Stochastic Conformance Checking in Process Mining

no code implementations18 Jul 2020 Artem Polyvyanyy, Alistair Moffat, Luciano García-Bañuelos

Given an event log as a collection of recorded real-world process traces, process mining aims to automatically construct a process model that is both simple and provides a useful explanation of the traces.

Boosting Search Performance Using Query Variations

1 code implementation15 Nov 2018 Rodger Benham, Joel Mackenzie, Alistair Moffat, J. Shane Culpepper

Rank fusion is a powerful technique that allows multiple sources of information to be combined into a single result set.

Re-Ranking Retrieval

From Theory to Practice: Plug and Play with Succinct Data Structures

5 code implementations5 Nov 2013 Simon Gog, Timo Beller, Alistair Moffat, Matthias Petri

Engineering efficient implementations of compact and succinct structures is a time-consuming and challenging task, since there is no standard library of easy-to- use, highly optimized, and composable components.

Data Structures and Algorithms

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