US 8,543,565 B2Granted

System and method using a discriminative learning approach for question answering

AssigneeAT&T Intellectual Property II, L.P.

InventorJunlan Feng

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Abstract

Disclosed are systems, methods, and computer readable media for answers to natural language questions. The method embodiment comprises training a lexical association model between a question and a first set of one or more possible answers, training a semantic association model between a question and a second set of one or more possible answers, receiving a user question containing at least one query word, parsing the user question syntactically and semantically, formulating a query from the parsed user question containing at least one query word, expanding the query based on the lexical association model and the semantic association model, weighting the at least one query word according to its importance when answering the user question, and returning an answer based on the weighted at least one query word, the lexical association model, and the semantic association model. Other features include using question-answer pairs mined to train the models and returning a plurality of answers in an order based on the lexical association model and the semantic association model.

Claims20

Dependent claims

A method comprising:

training a lexical association model between a question and a first set of possible answers;
training a semantic association model between the question and a second set of possible answers;
receiving a user question containing query words;
parsing the user question syntactically and semantically, to yield a parsed user question;
expanding the query words based on the lexical association model and the semantic association model, to yield expanded query words;
weighting the expanded query words according to importance when answering the user question, to yield a weighted expanded query words;
and returning an answer based on a score calculated based on the following equation:
score
⁡
(
q
,
a
)
=
∑
w
∈
q
,
a
⁢
docf
⁡
(
w
,
q
,
a
)
*
qf
⁡
(
w
)
+
∑
ne
∈
NE
⁡
(
qp
)
,
qp
∈
q
⁢
docf
⁡
(
ne
,
q
,
a
)
*
λ
sem
⁡
(
qp
,
ne
)
+
∑
v
∈
Exp
⁡
(
w
)
,
w
∈
q
,
v
∈
a
⁢
docf
⁡
(
v
,
q
,
a
)
*
λ
lex
⁡
(
w
,
v
)
wherein docf represents a normalized frequency distribution function, w represents individual query words, q represents individual questions, a represents individual answers, NE represents a set of named entity tags, ne represents individual named entity tags, qp represents a question phrase, v represents an answer word, w represents a query word, λsem represents a semantic association parameter, λlex represents a lexical association parameter, and qf represents the weighted expanded query words.

103 more elements

Dependencies are inferred from the claim text.