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SEMANTIC SIMILARITY THESIS

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Article Metrics Contributions to Semantic Textual Similarity Algorithms
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Master's Theses. Bioinformatics Commons , Theory and Algorithms Commons.
Advanced Search. However, sentences similarity models are still an immature
research field. This thesis introduces innovative elements to standard
paradigms, trying to improve the performances of the implemented models in terms
of accuracy. The first and simplest model determines whether the broad class
anchor give plays a significant role within a particular narrow class; the
second can test whether a narrow class anchor has a significant effect in
addition to the effect of the broad class anchor.

The give class data set consists of 5, sentences occurring with 13 distinct pay,
sell, hand, lend, feed, serve, lease, repay, loan, rent, refund, peddle, and
trade. As before, sentences that contain the anchor verb give were excluded from
the analysis. For this class, we can only test whether previous findings can be
replicated within this smaller set of verbs as the narrow class anchor is the
same as the anchor for the entire set of alternating verbs. This model showed
that all four predictors make independent contributions to predicting the choice
of syntactic frame, i.

Not too surprisingly, and in line with our Narrow Verb Anchor Hypothesis, the
results show that give serves as anchor to the narrow give class just as it did
for the broad class of alternating verbs.


ARTICLE METRICS

The data set for the message transfer class includes 2, sentences occurring with
9 non- tell verbs show, ask, write, teach, read, pose, quote, preach, and cite.
When both similarity to give and residual similarity to the narrow class anchor
tell were entered in the model, the two similarity predictors both turned out to
be significant and, notably, both in the positive direction as predicted i.

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The future having class data set consists of 5, sentences occurring with 17
different verbs, excluding sentences with the narrow class anchor leave offer,
owe, extend, grant, assign, award, allocate, issue, promise, guarantee, advance,
concede, yield, bequeath, cede, allot, and will. In the analyses we just
presented, we used residual semantic similarity to narrow class anchors as
predictors to account for featural overlap between broad and narrow class
anchors, as our narrow class anchor hypothesis focuses on the effect on
syntactic frame selection of features verbs of a narrow class share with their
respective narrow class anchors but not with give.

Wurm and Fisicaro , though, suggest using unresidualized predictors for multiple
regression analyses that include strongly correlated predictors. We therefore
also tested a model where both similarity to give and unresidualized similarity
to the narrow class anchor were predictors.

To summarize, we showed that give serves as the broad class anchor of the
ditransitive frame for each of the three narrow verb classes and that the
residual portion of narrow class anchors may assist e. The narrow class analyses
should be taken with some caution, as the narrow class analyses are based on a
relatively small number of verbs and we therefore cannot be sure, at this point,
whether our results will generalize. Despite these limitations, our analysis of
narrow class anchors suggests that they too play a role in syntactic frame
selection independently of or cooperatively with broad class anchors.

This paper quantitatively investigated one of the causes behind verb structural
preferences when overall meaning is kept relatively constant across a pair of
syntactic frames. Drawing insight from the categorization literature and the
notion of exemplars, we treated syntactic frames as categories and sentences
occurring in those frames, more specifically verbs that occur in sentences, as
exemplars.

We hypothesized that frequent experience with exemplar sentences where a
particular verb occurs in a particular syntactic frame may lead to a strong
association between the verb and the frame, analogous to the association between
a category and its best exemplar e. Medin and Schaffer Categorization research
showed that similarity to the best exemplar is a critical factor for an entity
to be considered a member of the category the best exemplar belongs to. We
tested the Verb Anchor Hypothesis by investigating sentences that include verbs
participating in the dative alternation.

Our main predictor was semantic similarity between the ditransitive anchor verb
give and other alternating verbs, as estimated by Latent Semantic Analysis. To
summarize our results, semantic similarity to the anchor give is a significant
predictor of syntactic frame selection and the effect of this predictor is not
reducible to that of other factors such as the presence of a caused possession
entailment in both frames or pronominality of postverbal arguments. Overall, our
results confirm our hypothesis that semantic similarity to the verb most
strongly associated with a syntactic frame modulates syntactic frame selection.

We also tested our Verb Anchor Hypothesis on semantically more cohesive narrow
classes like those discussed in Pinker and showed that narrow class anchors can
also play a role in predicting syntactic frame selection. Of particular note is
the fact that narrow class anchors may counteract the effect of broad class
anchors: While give pulls future having verbs to the ditransitive frame, leave
pulls them in the opposite direction, namely to the prepositional frame.

Many researchers have pointed out that verbs occurring particularly frequently
in a certain syntactic frame tend to have a very general meaning e. Since give
occurs both highly frequently in the ditransitive frame and its meaning is
indeed quite general and not much more than the notion of transfer of possession
many assign to the ditransitive frame, teasing apart these two hypotheses is
hard.

The results of our analysis of the narrow class anchors, though, suggest that
the mechanisms underlying the effect of verb anchors amount to more than the
semantic generality of verbs like give and provide support for the effect of
frequency of occurrence of verbs in particular frames. Namely, leave pull class
members towards the prepositional frame, not towards the ditransitive frame as
give does. The results of our narrow class models also suggest that our focus on
a single anchor for the ditransitive frame might be an oversimplification of the
role of semantic similarity in sentence production.

Verbs overlap in meaning with many verbs, not just the verb that occurs most
frequently in a syntactic frame: The verb that best expresses the situation
category that a speaker wishes to communicate activates many other verbs.

Each of these verbs activates the syntactic frames they occur in. It is
justified theoretically by previous claims about the importance of verbs that
occur most frequently in syntactic frames in the acquisition e. Pinker ;
Goldberg of argument structure constructions. Second, and more practically, the
effect of most verbs other than anchors may be too small to be measurable, as
the strength of their association with a syntactic frame may be quite weak.

Starting the investigation of the influence of semantic similarity on syntactic
frame selection with most frequently occurring verbs is, we believe, the wisest
course of action. Not only is the behavior to be explained different, so are the
predictors. Also, our model, as mentioned in the introduction, does not assume
that syntactic frames have meanings. Nor does it rely on a theory of meaning
that probabilistically include features from the meaning of all verbs that occur
in the syntactic frame. Our hypothesis relies on the more conservative view that
lexical semantic overlap is what leads to the activation of other concepts, an
assumption critical to explaining semantic priming effects McRae and Boisvert
Another issue we would like to tackle is whether the effect of anchor verbs on
syntactic frame selection is a peculiarity of the dative alternation or can be
generalized to other syntactic frames.

As one reviewer pointed out, other verbs have been argued to be typical
exemplars of argument structure constructions, e. The Verb Anchor Hypothesis
predicts that such verbs should attract semantically similar verbs to occur in
the construction they are typical exemplars of. The results of a model we ran on
the 45 verbs listed in Levin as participating in the locative alternation
suggest that this prediction is borne out.

John spayed the powder on the wall vs. John sprayed the wall with the powder.
Despite this result, whether the Verb Anchor Hypothesis applies to most
alternations or just a few depends on several factors whose effect we cannot at
present ascertain and is thus a matter for further study. As Sun and Koenig and
Sun point out, the verb frequency distribution observed in the dative
alternation is rather unique among English verb alternations. We thank members
of the Department of Linguistics and the Psycholinguistic Lab at the University
at Buffalo for their feedback on the research reported in this paper.

We extend our gratitude to Aron Marvel for his help in collecting some of the
data. Finally, we wish to thank the anonymous reviewers and the editors of
Cognitive Linguistics for their comments and suggestions. Aiken, Leona S.
Multiple regression: Testing and interpreting interactions. London: Sage
Publications. Ambridge, Ben, Julian M. Pine, Caroline F. Avoiding dative
overgeneralisation errors: Semantics, statistics or both? Language, Cognition
and Neuroscience 29 2.

Baayen, R. Harald, Laurie B. Morphological influences on the recognition of
monosyllabic monomorphemic words. Journal of Memory and Language Harald Baayen.
Predicting the dative alternation. Amsterdam: Royal Netherlands Academy of
Science.


CONTRIBUTIONS TO SEMANTIC TEXTUAL SIMILARITY ALGORITHMS

Word Frequency. New York: Houghton Mifflin.

 * english essay grammar checker.
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Casenhiser, Devin M. Fast mapping between a phrasal form and meaning.
Developmental Science 8 6. Chang, Franklin, Gary S. Becoming syntactic.
Psychological Review 2. Charniak, Eugene. Statistical parsing with a
context-free grammar and word statistics. Proceedings of the fourteenth national
conference on artificial intelligence AAAI , — American Association for
Artificial Intelligence. Clark, Eve V. Discovering what words can do.
Parasession on the lexicon, Proceedings of the Chicago Linguistics Society
Collins, Peter. The indirect object construction in English: An informational
approach.

Linguistics Deerwester, Scott, Susan T. Dumais, George W. Furnas, Thomas K.
Indexing by Latent Semantic Analysis. Many proteins are annotated with very
generic terms inside the GO shallow annotations. These annotations do not
identify the specific role or function of the protein, but only suggest the area
in which the proteins operate. Shallow annotations heavily affect the fact of SS
measures. Since proteins are often annotated with very generic terms in the GO,
many proteins will share one or more very generic terms.

However, the fact that two proteins share generic terms does not imply that they
are closely related.


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Volume 24 Issue 4 Novpp. Document classification using semantic networks with an
adaptive similarity measure Filip Ginter, Sampo Pyysalo, Tapio SalakoskiIn
Amsterdam studies in the theory and history of linguistic science
seriesCiteseervolume Cognitive Science This section presents some existing tools
implementing SS measures. They usually are the first verbs to be learned by
children Clark and considered to play a significant role in second language
acquisition as they serve as prototypical verbs for particular syntactic frames.
Community curation of bioinformatics software and data resources. Such analysis
revealed the applicability of SS measures for PPI network reconstruction
problems and for semantic similarity thesis clustering. Ontological analysis of
gene expression data: current tools, limitations, and open problems. Some
features of this site may not work without it. Li, D. In the Ditransitive or
Double Object frame 1awhich give occurs most frequently in, the recipient
argument is realized as an NP and precedes the gift argument realized also as
NP. Therefore, in general we suggest to use IEA annotations, especially for
large-scale studies. Note that verbs in these three narrow classes are all give
-type semantic similarity thesis that invariably entail caused possession in
both the ditransitive and prepositional frames Rappaport Hovav and Levin

SS measures have to keep into account this fact.

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Department of Cybernetics. Master's Thesis. Semantic Sentence Similarity for
Intent Recognition Task. Tomáš Brich @