Variation i kvinnors namnfraser i officiella dokument i Helsingfors 1780-1930 : Socioonomastiska synvinklar på makt och identitet

This dissertation is an onomastic study of variation in women s name phrases in official documents in Finland during the period 1780−1930. The aim is to discuss from a socio-onomastic perspective both the changeover from patronymics to inherited family names and the use of surnames after marriage (i.e. whether women adopted their husbands family names or retained their maiden names), before new laws in this area entered into force in Finland in the early 20th century. In 1920, a law on family names that required fixed names put an end to the use of the patronymic as a person s only surname. After 1929, it was no longer possible for a married woman to retain her maiden name. Methodologically, to explain this development from a socio-onomastic perspective, I have based my study on a syntactic-semantic analysis of the actual name phrases. To be able to demonstrate the extensive material, I have elaborated a scheme to divide the 115 different types of name phrases into 13 main categories. The analysis of the material for Helsinki is based on frequency calculations of the different types of name phrases every thirtieth year, as well as on describing variation in the structure and semantic content of the name phrases, e.g. social variation in the use of titles and epithets. In addition to this, by applying a biographic-genealogical method, I have conducted two case studies of the usage of women s name phrases in the two chosen families. The study is based on parish registers from the period 1780−1929, estate inventory documents from the period 1780−1928, registration forms for liberty of trade from the period 1880−1908, family announcements on newspapers from the period 1829−1888, gravestones from the period 1796−1929 and diaries from the periods 1799−1801 and 1818−1820 providing a corpus of 5 950 name phrases. The syntactic-semantic analysis has revealed the overall picture of various ways of denoting women in official documents. In Helsinki, towards the end of the 19th century, the use of inherited family names seems to be almost fully developed in official contexts. At the late 19th century, a patronymic still appears as the only surname of some working-class women whereas in the early 20th century patronymics were only entered in the parish register as a kind of middle name. In the beginning of the 19th century, most married women were still registered under their maiden names, with a few exceptions among the bourgeoisie and upper class. The comparative analysis of name phrases in diaries, however, indicates that the use of the husband s family name by married women was a much earlier phenomenon in private contexts than in official documents. Keywords: socio-onomastics, syntactic-semantic analysis, name phrase, patronymic, maiden name, husband s family name

Analisi contrastiva delle modalità di traduzione in finnico dei Tempi verbali e delle perifrasi aspettuali dell'italiano

Analisi contrastiva delle modalità di traduzione in finnico dei Tempi verbali e delle perifrasi aspettuali dell italiano (Italian Philology) The topic of this research is a contrastive study of tenses and aspect in Italian and in Finnish. The study aims to develop a research method for analyzing translations and comparable texts (non-translation) written in a target language. Thus, the analysis is based on empirical data consisting of translations of novels from Italian to Finnish and vice versa. In addition to this, for the section devoted to solutions adopted in Finnish for translating the Italian tenses Perfetto Semplice and Perfetto Composto, 39 Finnish native speakers were asked to answer questions concerning the choice of Perfekti and Imperfekti in Finnish. The responses given by the Finnish informants were compared to the choices made by translators in the target language, and in this way it was possible both to benefit from the motivation provided by native speakers to explain the selection of a tense (Imperfekti/Perfekti) in a specific context compared with the Italian formal equivalents (Perfetto Composto/Perfetto Semplice), and to define the specific features of the Finnish verb tenses. The research aims to develop a qualitative method for the analysis of formal equivalents and translational changes ( shifts ). Although, as the choice of Italian and Finnish progressive forms is optional and related to speaker preferences, besides the qualitative analysis, I also considered it necessary to operate a quantitative one in order to find out whether the two items share the same degree of correspondence in frequency of use. In this study I explain translation choices in light of cognitive grammar, suggesting that particular translation relationships derive from so-called construal operations. I use the concepts of cognitive linguistics not only to analyze the convergences and divergences of the two aspectual systems, but also to redefine some general procedures related to the phenomenon of translation. For the practical analysis of the corpus were for the most part employed theoretical categories developed in a framework proposed by Pier Marco Bertinetto. Following this approach, the notions of aspect (the morphologic or morphosyntactic, subjective level) and actionality (the lexical aspect or objective level, traditionally Aktionsart) are carefully distinguished. This also allowed me to test the applicability of these distinctions to two languages typologically different from each other. The data allowed both the analysis of the semantic and pragmatic features that determine tense and aspect choices in these two languages, and to discover the correspondences between the two language systems and the strategies that translators are forced to resort to in particular situations. The research provides not only a detailed and analytically argued inventory about possible solutions for translating Italian tenses and aspectual devices in Finnish that could be of pedagogical relevance, but also new contributions about the specific uses of time-aspectual devices in the two languages in question.

Cohésion modale et subordination : Le conditionnel et le jussif finnois au miroir de la valeur sémantique et discursive du subjonctif français

Modal cohesion and subordination. The Finnish conditional and jussive moods in comparison to the French subjunctive This study examines verb moods in subordinate clauses in French and Finnish. The first part of the analysis deals with the syntax and semantics of the French subjunctive, mood occurring mostly in subordinate positions. The second part investigates Finnish verb moods. Although subordinate positions in Finnish grammar have no special finite verb form, certain uses of Finnish verb moods have been compared to those of subjunctives and conjunctives in other languages. The present study focuses on the subordinate uses of the Finnish conditional and jussive (i.e. the third person singular and plural of the imperative mood). The third part of the analysis discusses the functions of subordinate moods in contexts beyond complex sentences. The data used for the analysis include 1834 complex sentences gathered from newspapers, online discussion groups and blog texts, as well as audio-recorded interviews and conversations. The data thus consist of both written and oral texts as well as standard and non-standard variants. The analysis shows that the French subjunctive codes theoretical modality. The subjunctive does not determine the temporal and modal meaning of the event, but displays the event as virtual. In a complex sentence, the main clause determines the temporal and modal space within which the event coded by the subjunctive clause is interpreted. The subjunctive explicitly indicates that the space constructed in the main clause extends its scope over the subordinate clause. The subjunctive can therefore serve as a means for creating modal cohesion in the discourse. The Finnish conditional shares the function of making explicit the modal link between the components of a complex construction with the French subjunctive, but the two moods differ in their semantics. The conditional codes future time and can therefore occur only in non-factual or counterfactual contexts, whereas the event expressed by French subjunctive clauses can also be interpreted as realized. Such is the case when, for instance, generic and habitual meaning is involved. The Finnish jussive mood is used in a relatively limited number of subordinate clause types, but in these contexts its modal meaning is strikingly close to that of the French subjunctive. The permissive meaning, typical of the jussive in main clause positions, is modified in complex sentences so that it entails inter-clausal relation, namely concession. Like the French subjunctive, the jussive codes theoretical modal meaning with no implication of the truth value of the proposition. Finally, the analysis shows that verb moods mark modal cohesion, not only on the syntagmatic level (namely in complexe sentences), but also on the paradigmatic axis of discourse in order to create semantic links over entire segments of talk. In this study, the subjunctive thus appears, not as an empty category without function, as it is sometimes described, but as an open form that conveys the temporal and modal meanings emerging from the context.

Neurocognitive processing of inflected and derived words

The representation of morphologically complex words in the mental lexicon and their neurocognitive processing has been a vigorously debated topic in psycholinguistics and the cognitive neuroscience of language. This thesis investigates the effect of stimulus modality on morphological processing, the spatiotemporal dynamics of the neural processing of inflected (e.g., work+ed ) and derived (e.g., work+er ) words and their interaction, using the Finnish language. Overall, the results suggest that the constituent morphemes of isolated written and spoken inflected words are accessed separately, whereas spoken derived words activate both their full form and the constituent morphemes. The processing of both spoken and written inflected words elicited larger N400 responses than monomorphemic words (Study I), whereas the responses to spoken derived words did not differ from those to monomorphemic words (Study IV). Spoken inflected words elicited a larger left-lateralized negativity and greater source strengths in the left temporal cortices than derived words (Study IV). Thus, the results suggest different cortical processing for derived and inflected words. Moreover, the neural mechanisms underlying inflection and derivation seem to be not only different, but also independent as indexed by the linear summation of the responses to derived and inflected stimuli in a combined (derivation+inflection) condition (Study III). Furthermore, the processing of meaningless, spoken derived pseudowords was more difficult than for existing derived words, indexed by a larger N400-type effect for the pseudowords. However, no differences were observed between meaningful derived pseudowords and existing derived words (Study II). The results of Study II suggest that semantic compatibility between morphemes seems to have a crucial role in a successful morphological analysis. As a methodological note, time-locking the auditory event-related potentials/fields (ERP/ERF) to the suffix onset revealed the processes related to morphological analysis more precisely (Studies II and IV), which also enables comparison of the neural processes in different modalities (Study I).

Do wordnets also improve human performance on NLP tasks?

FinnWordNet is a wordnet for Finnish that complies with the format of the Princeton WordNet (PWN) (Fellbaum, 1998). It was built by translating the PrincetonWordNet 3.0 synsets into Finnish by human translators. It is open source and contains 117000 synsets. The Finnish translations were inserted into the PWN structure resulting in a bilingual lexical database. In natural language processing (NLP), wordnets have been used for infusing computers with semantic knowledge assuming that humans already have a sufficient amount of this knowledge. In this paper we present a case study of using wordnets as an electronic dictionary. We tested whether native Finnish speakers benefit from using a wordnet while completing English sentence completion tasks. We found that using either an English wordnet or a bilingual English Finnish wordnet significantly improves performance in the task. This should be taken into account when setting standards and comparing human and computer performance on these tasks.

FinnWordNet - WordNet på finska via översättning

FinnWordNet is a WordNet for Finnish that conforms to the framework given in Fellbaum (1998) and Vossen (ed.) (1998). FinnWordNet is open source and currently contains 117,000 synsets. A classic WordNet consists of synsets, or sets of partial synonyms whose shared meaning is described and exemplified by a gloss, a common part of speech and a hyperonym. Synsets in a WordNet are arranged in hierarchical partial orderings according to semantic relations like hyponymy/hyperonymy. Together the gloss, part of speech and hyperonym fix the meaning of a word and constrain the possible translations of a word in a given synset. The Finnish group has opted for translating Princeton WordNet 3.0 synsets wholesale into Finnish by professional translators, because the translation process can be controlled with regard to quality, coverage, cost and speed of translation. The project was financed by FIN-CLARIN at the University of Helsinki. According to our preliminary evaluation, the translation process was diligent and the quality is on a par with the original Princeton WordNet.

Discovery of Application Workloads from Network File Traces

An understanding of application I/O access patterns is useful in several situations. First, gaining insight into what applications are doing with their data at a semantic level helps in designing efficient storage systems. Second, it helps create benchmarks that mimic realistic application behavior closely. Third, it enables autonomic systems as the information obtained can be used to adapt the system in a closed loop.All these use cases require the ability to extract the application-level semantics of I/O operations. Methods such as modifying application code to associate I/O operations with semantic tags are intrusive. It is well known that network file system traces are an important source of information that can be obtained non-intrusively and analyzed either online or offline. These traces are a sequence of primitive file system operations and their parameters. Simple counting, statistical analysis or deterministic search techniques are inadequate for discovering application-level semantics in the general case, because of the inherent variation and noise in realistic traces.In this paper, we describe a trace analysis methodology based on Profile Hidden Markov Models. We show that the methodology has powerful discriminatory capabilities that enable it to recognize applications based on the patterns in the traces, and to mark out regions in a long trace that encapsulate sets of primitive operations that represent higher-level application actions. It is robust enough that it can work around discrepancies between training and target traces such as in length and interleaving with other operations. We demonstrate the feasibility of recognizing patterns based on a small sampling of the trace, enabling faster trace analysis. Preliminary experiments show that the method is capable of learning accurate profile models on live traces in an online setting. We present a detailed evaluation of this methodology in a UNIX environment using NFS traces of selected commonly used applications such as compilations as well as on industrial strength benchmarks such as TPC-C and Postmark, and discuss its capabilities and limitations in the context of the use cases mentioned above.

Fuzzy Clustering Based Ad Recommendation for TV Programs

Advertisements(Ads) are the main revenue earner for Television (TV) broadcasters. As TV reaches a large audience, it acts as the best media for advertisements of products and services. With the emergence of digital TV, it is important for the broadcasters to provide an intelligent service according to the various dimensions like program features, ad features, viewers’ interest and sponsors’ preference. We present an automatic ad recommendation algorithm that selects a set of ads by considering these dimensions and semantically match them with programs. Features of the ad video are captured interms of annotations and they are grouped into number of predefined semantic categories by using a categorization technique. Fuzzy categorical data clustering technique is applied on categorized data for selecting better suited ads for a particular program. Since the same ad can be recommended for more than one program depending upon multiple parameters, fuzzy clustering acts as the best suited method for ad recommendation. The relative fuzzy score called “degree of membership” calculated for each ad indicates the membership of a particular ad to different program clusters. Subjective evaluation of the algorithm is done by 10 different people and rated with a high success score.

Automatic extraction of free-form surface features (FFSFs)

This paper presents a new algorithm for extracting Free-Form Surface Features (FFSFs) from a surface model. The extraction algorithm is based on a modified taxonomy of FFSFs from that proposed in the literature. A new classification scheme has been proposed for FFSFs to enable their representation and extraction. The paper proposes a separating curve as a signature of FFSFs in a surface model. FFSFs are classified based on the characteristics of the separating curve (number and type) and the influence region (the region enclosed by the separating curve). A method to extract these entities is presented. The algorithm has been implemented and tested for various free-form surface features on different types of free-form surfaces (base surfaces) and is found to correctly identify and represent the features irrespective of the type of underlying surface. The representation and extraction algorithm are both based on topology and geometry. The algorithm is data-driven and does not use any pre-defined templates. The definition presented for a feature is unambiguous and application independent. The proposed classification of FFSFs can be used to develop an ontology to determine semantic equivalences for the feature to be exchanged, mapped and used across PLM applications. (C) 2011 Elsevier Ltd. All rights reserved.

Kannada WordNet - a lexical database

This paper presents the preliminary analysis of Kannada WordNet and the set of relevant computational tools. Although the design has been inspired by the famous English WordNet, and to certain extent, by the Hindi WordNet, the unique features of Kannada WordNet are graded antonyms and meronymy relationships, nominal as well as verbal compoundings, complex verb constructions and efficient underlying database design (designed to handle storage and display of Kannada unicode characters). Kannada WordNet would not only add to the sparse collection of machine-readable Kannada dictionaries, but also will give new insights into the Kannada vocabulary. It provides sufficient interface for applications involved in Kannada machine translation, spell checker and semantic analyser.

Combining heterogeneous classifiers for relational databases

Practical usage of machine learning is gaining strategic importance in enterprises looking for business intelligence. However, most enterprise data is distributed in multiple relational databases with expert-designed schema. Using traditional single-table machine learning techniques over such data not only incur a computational penalty for converting to a flat form (mega-join), even the human-specified semantic information present in the relations is lost. In this paper, we present a practical, two-phase hierarchical meta-classification algorithm for relational databases with a semantic divide and conquer approach. We propose a recursive, prediction aggregation technique over heterogeneous classifiers applied on individual database tables. The proposed algorithm was evaluated on three diverse datasets. namely TPCH, PKDD and UCI benchmarks and showed considerable reduction in classification time without any loss of prediction accuracy. (C) 2012 Elsevier Ltd. All rights reserved.

Exploiting coherence for the simultaneous discovery of latent facets and associated sentiments

Facet-based sentiment analysis involves discovering the latent facets, sentiments and their associations. Traditional facet-based sentiment analysis algorithms typically perform the various tasks in sequence, and fail to take advantage of the mutual reinforcement of the tasks. Additionally,inferring sentiment levels typically requires domain knowledge or human intervention. In this paper, we propose aseries of probabilistic models that jointly discover latent facets and sentiment topics, and also order the sentiment topics with respect to a multi-point scale, in a language and domain independent manner. This is achieved by simultaneously capturing both short-range syntactic structure and long range semantic dependencies between the sentiment and facet words. The models further incorporate coherence in reviews, where reviewers dwell on one facet or sentiment level before moving on, for more accurate facet and sentiment discovery. For reviews which are supplemented with ratings, our models automatically order the latent sentiment topics, without requiring seed-words or domain-knowledge. To the best of our knowledge, our work is the first attempt to combine the notions of syntactic and semantic dependencies in the domain of review mining. Further, the concept of facet and sentiment coherence has not been explored earlier either. Extensive experimental results on real world review data show that the proposed models outperform various state of the art baselines for facet-based sentiment analysis.

Diversity in ranking via resistive graph centers

Users can rarely reveal their information need in full detail to a search engine within 1--2 words, so search engines need to "hedge their bets" and present diverse results within the precious 10 response slots. Diversity in ranking is of much recent interest. Most existing solutions estimate the marginal utility of an item given a set of items already in the response, and then use variants of greedy set cover. Others design graphs with the items as nodes and choose diverse items based on visit rates (PageRank). Here we introduce a radically new and natural formulation of diversity as finding centers in resistive graphs. Unlike in PageRank, we do not specify the edge resistances (equivalently, conductances) and ask for node visit rates. Instead, we look for a sparse set of center nodes so that the effective conductance from the center to the rest of the graph has maximum entropy. We give a cogent semantic justification for turning PageRank thus on its head. In marked deviation from prior work, our edge resistances are learnt from training data. Inference and learning are NP-hard, but we give practical solutions. In extensive experiments with subtopic retrieval, social network search, and document summarization, our approach convincingly surpasses recently-published diversity algorithms like subtopic cover, max-marginal relevance (MMR), Grasshopper, DivRank, and SVMdiv.

Assessment of the Relationships Among Design Methods, Design Activities, and Creativity

This paper presents an experimental study that was conducted to compare the results obtained from using different design methods (brainstorming (BR), functional analysis (FA), and SCAMPER) in design processes. The objectives of this work are twofold. The first was to determine whether there are any differences in the length of time devoted to the different types of activities that are carried out in the design process, depending on the method that is employed; in other words, whether the design methods that are used make a difference in the profile of time spent across the design activities. The second objective was to analyze whether there is any kind of relationship between the time spent on design process activities and the degree of creativity in the solutions that are obtained. Creativity evaluation has been done by means of the degree of novelty and the level of resolution of the designed solutions using creative product semantic scale (CPSS) questionnaire. The results show that there are significant differences between the amounts of time devoted to activities related to understanding the problem and the typology of the design method, intuitive or logical, that are used. While the amount of time spent on analyzing the problem is very small in intuitive methods, such as brainstorming and SCAMPER (around 8-9% of the time), with logical methods like functional analysis practically half the time is devoted to analyzing the problem. Also, it has been found that the amount of time spent in each design phase has an influence on the results in terms of creativity, but results are not enough strong to define in which measure are they affected. This paper offers new data and results on the distinct benefits to be obtained from applying design methods. DOI: 10.1115/1.4007362]

Compressive sensing for music signals: comparison of transforms with coherent dictionaries

Compressive Sensing (CS) is a new sensing paradigm which permits sampling of a signal at its intrinsic information rate which could be much lower than Nyquist rate, while guaranteeing good quality reconstruction for signals sparse in a linear transform domain. We explore the application of CS formulation to music signals. Since music signals comprise of both tonal and transient nature, we examine several transforms such as discrete cosine transform (DCT), discrete wavelet transform (DWT), Fourier basis and also non-orthogonal warped transforms to explore the effectiveness of CS theory and the reconstruction algorithms. We show that for a given sparsity level, DCT, overcomplete, and warped Fourier dictionaries result in better reconstruction, and warped Fourier dictionary gives perceptually better reconstruction. “MUSHRA” test results show that a moderate quality reconstruction is possible with about half the Nyquist sampling.