Labs

Research

Our technology is based on 15+ years of research in computational linguistics and computer science. We believe that you cannot make any significant progress unless you push the boundaries and break new ground. Our lab is constantly refining and advancing our algorithms and methodologies. We work in two main areas of research:

Distributional semantics, a research area in which we develop and study theories and methods for quantifying and categorising semantic similarities between linguistic items based on their distributional properties in large samples of language data. Our interest here is manifold: we work on algorithms for the effective acquisition of understanding from text, on rich and useful representations for linguistic content and situational context, and on applications of distributional models to real world tasks (obviously, mostly tasks of commercial interest to us).

Evaluation of learning language models, finding methods and metrics to test and compare algorithms, memory models, and processing approaches, both to benchmark improvements and to validate approaches with respect to tasks of interest.

Publications

  • Developing a Swedish Language Datalab

    Gavagai participates as a stakeholder in a VINNOVA-funded project on creating data resources for language technology research. Gavagai will during the course of the project develop an open-source software kit that enables language models to be trained on data that is not made public. This is useful for when a data resource cannot be shared …

  • The language of smell: Connecting linguistic and psychophysical properties of odor descriptors

    The olfactory sense is a particularly challenging domain for cognitive science investigations of perception, memory, and language. Although many studies show that odors often are difficult to describe verbally, little is known about the associations between olfactory percepts and the words that describe them. Quantitative models of how odor experiences are described in natural language …

  • Authorship profiling without using topical information

    This paper describes an experiment made for the PAN 2018 shared task on author profiling. The task is to distinguish female from male authors of microblog posts published on Twitter using no extraneous information except what is in the posts; this experiment focusses on using non-topical information from the posts, rather than gender differences in …

  • Hyperdimensional utterance spaces

    Human language has a large and varying number of features, both lexical items and constructions, which interact to represent various aspects of communicative information. High-dimensional semantic spaces have proven useful and effective for aggregating and processing lexical information for many language processing tasks. This paper describes a hyperdimensional processing model for language data, a straightforward …

  • The Smart Data Layer

    This paper introduces the notion of a smart data layer for the Internet of Everything. The smart data layer can be seen as an AI that learns a generic representation from heterogeneous data streams with the goal of understanding the state of the user. The smart data layer can be used both as materials for …

  • Analysis of Open Answers to Survey Questions through Interactive Clustering and Theme Extraction

    This paper describes design principles for and the implementation of Gavagai Explorer—a new application which builds on interactive text clustering to extract themes from topically coherent text sets such as open text answers to surveys or questionnaires.An automated system is quick, consistent, and has full coverage over the study material. A system allows an analyst …

  • Practical Issues in Information Access System Evaluation

    This paper is a report from a workshop on Evaluation of Information Systems in Commercial Settings, inspired by the industrial day at SIGIR 2016. Small and medium size enterprises often lack the resources needed to develop proper evaluation infrastructures, but also to follow the research development in the field of evaluation. Similarly,academics lag behind in …

  • Plausibility Testing for Lexical Resources

    This paper describes principles for evaluation metrics for lexical components using randomly scrambled sentences compared with naturally occurring ones, and sentences where some salient referent has been replaces with a liar’s item, together with a pilot implementation of those principles based on requirements from practical information system

  • A proposal to use distributional models to analyse dolphin vocalization

    This paper gives a brief introduction to the starting points of our coming—pending favourable decisions by research funding agencies—experimental project to study dolphin communicative behaviour using distributional semantics as implemented by us at Gavagai. It presents some of the challenges and conveys some of the optimism we feel is warranted given the rapid increase of …

  • Random indexing of multidimensional data

    This paper gives a model for how to generalise random indexing to multidimensional arrays and therefore enable approximation of higher-order statistical relationships in data. The generalised method is a sparse implementation of random projections, which is the theoretical basis also for ordinary random indexing and other randomisation approaches to dimensionality reduction and data representation. We …

  • En rekommenderad svensk språkteknologisk terminologi

    In 2014 the Swedish Language Technology Terminology Group was created, with representatives from different parts of the language technology community, both higher education and research, industry and governmental agencies. In 2016 we have recommended Swedish terms for the 270 language technological concepts in the Bank of Finnish Terminology in Arts and Sciences. The language technology …

  • Evaluating Categorisation in Real Life – an argument against simple but impractical metrics

    Text categorisation in commercial application poses several limiting constraints on the technology solutions to be employed. This paper describes how a method with some potential improvements is evaluated for practical purposes and argues for a richer and more expressive evaluation procedure. In this paper one such method is exemplified by a precision-recall matrix which exchanges …

  • Dead Man Tweeting

    This paper presents our first take at a text generator: Dead Man Tweeting, a system that learns semantic avatars from (dead) people’s texts, and makes the avatars come alive on Twitter. The system includes a language model for generating sequences of words, a topic model for ensuring that the sequences are topically coherent, and a …

  • The Gavagai Living Lexicon

    This paper presents the Gavagai Living Lexicon, which is an online distributional semantic model currently available in 20 different languages. We describe the underlying distributional semantic model, and how we have solved some of the challenges in applying such a model to large amounts of streaming data. We also describe the architecture of our implementation, …

  • Detecting Speculations, Contrasts and Conditionals in Consumer Reviews

    A support vector classifier was compared to a lexicon-based approach for the task of detecting the stance categories speculation, contrast and conditional in English consumer reviews. Around 3,000 training instances were required to achieve a stable performance of an F-score of 90 for speculation. This outperformed the lexicon-based approach, for which an F-score of just …

  • Factorization of Latent Variables in Distributional Semantic Models

    This paper discusses the use of factorization techniques in distributional semantic models. We focus on a method for redistributing the weight of latent variables, which have previously been shown to improve the performance of distributional semantic models. However, this result has not been replicated and remains poorly understood. We refine the method, and provide additional …

  • Navigating the Semantic Horizon using Relative Neighborhood Graphs

    This paper introduces a novel way to navigate neighborhoods in distributional semantic models. The approach is based on relative neighborhood graphs, which uncover the topological structure of local neighborhoods in semantic space. This has the potential to overcome both the problem with selecting a proper k in k-NN search, and the problem that a ranked …

  • Frontiers, Challenges, and Opportunities for Information Retrieval – Report from SWIRL 2012, The Second Strategic Workshop on Information Retrieval in Lorne

    During a three-day workshop in February 2012, 45 Information Retrieval researchers met to discuss long-range challenges and opportunities within the field. The result of the workshop is a diverse set of research directions, project ideas, and challenge areas. This report describes the workshop format, provides summaries of broad themes that emerged, includes brief descriptions of all …

  • Inferring the location of authors from words in their texts

    This paper  describes a series of experiments to determine how positionally annotated Twitter texts can be used to learn words which indicate location of other texts and their authors. Many texts are locatable but most have no explicit indication of place — many applications, both commercial and academic, have an interest in knowning where a text or …

  • A Use Case Framework for Information Access Evaluation

    Despite that the need for a common evaluation framework for multimedia and multimodal documents for various use cases, including non-topical use, is widely acknowledged, such a framework is still not in place. Retrieval system evaluation results are not regularly validated in laboratory or field studies; the infrastructure for generalizing results over tasks, users and collections is still missing. This chapter …

  • Semantic Topology

    A reasonable requirement (among many others) for a lexical or semantic component in an information system is that it should be able to learn incrementally from the linguistic data it is exposed to, that it can distinguish between the topical impact of various terms, and that it knows if it knows stuff or not. We …

  • Temperature in the Word Space: Sense Exploration of Temperature Expressions using Word-Space Modelling

    This chapter deals with a statistical technique for sense exploration based on distributional semantics known as word space modelling. Word space models rely on feature aggregation, in this case aggregation of co-occurrence events, to build an aggregated view on the distributional behaviour of words. Such models calculate meaning similarity among words on the basis of …

  • The STAVICTA Group Report for RepLab 2014 Reputation Dimensions Task

    In this paper we present our experiments on the RepLab 2014 Reputation Dimension task. RepLab is a competitive challenge for Reputation Management Systems. RepLab 2014’s reputation dimensions task focuses on categorization of Twitter messages with regard to standard reputation dimensions (such as performance, leadership, or innovation). Our approach only relies on the textual content of tweets and ignores both …

  • Språket avslöjar hur vi röstar

    “Hur ser det politiska opinionsläget ut? Det går förstås att fråga väljarna. Men bättre är kanske att se vad de skriver. Nu är ett datorprogram väljarnas sympatier på spåren.”

  • Search and Exploration of X-Rated Information (SEXI 2013)

    Adult content is pervasive on the Web, has been a driving factor in the adoption of the Internet medium. It is responsible for a significant fraction of traffic and revenues, yet rarely attracts attention in research. We propose that the research questions surrounding adult content access behaviors are unique, and we believe interesting and valuable …

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